Problem,Task,DatasetName,NumCompounds,Unit,Type,Metric,DatasetSplit,License,DatasetDescription,TaskDescription,Reference
Single_instance_prediction,ADME,hlm,6013,,,,,Not specified,The metabolic stability of compounds in Human and Rat Liver Microsomes is a crucial parameter in early-stage drug development. ,"Binary classification. Given a drug SMILES string, predict the metabolic stability of the compound in Human and Rat Liver Microsomes.",
Single_instance_prediction,ADME,clearance_hepatocyte_az,1213,uL.min-1.(10^6 cells)-1,Regression,Spearman,Scaffold,CC BY 4.0,Compounds are classified as either stable or unstable based on their half-life. ,"Regression. Given a drug SMILES string, predict the activity of clearance.","AstraZeneca. Experimental in vitro Dmpk and physicochemical data on a set of publicly disclosed compounds (2016), Di, Li, et al. ÒMechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design.Ó European journal of medicinal chemistry 57 (2012): 441-448."
Single_instance_prediction,ADME,vdss_lombardo,1130,L/kg,Regression,Spearman,Scaffold,CC BY 4.0,"The volume of distribution at steady state (VDss) measures the degree of a drug's concentration in body tissue compared to concentration in blood. Higher VD indicates a higher distribution in the tissue and usually indicates the drug with high lipid solubility, low plasma protein binidng rate.","Regression. Given a drug SMILES string, predict the volume of distributon.","Lombardo, Franco, and Yankang Jing. ÒIn silico prediction of volume of distribution in humans. Extensive data set and the exploration of linear and nonlinear methods coupled with molecular interaction fields descriptors.Ó Journal of Chemical Information and Modeling 56.10 (2016): 2042-2052."
Single_instance_prediction,ADME,cyp2c19_veith,12665,,,,,CC BY 4.0,"The CYP P450 genes are essential in the breakdown (metabolism) of various molecules and chemicals within cells. A drug that can inhibit these enzymes would mean poor metabolism to this drug and other drugs, which could lead to drug-drug interactions and adverse effects. Specifically, the CYP2C19 gene provides instructions for making an enzyme called the endoplasmic reticulum, which is involved in protein processing and transport.","Binary Classification. Given a drug SMILES string, predict CYP2C19 inhibition.","Veith, Henrike et al. ÒComprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.Ó Nature biotechnology vol. 27,11 (2009): 1050-5."
Single_instance_prediction,ADME,lipophilicity_astrazeneca,4200,,Regression,MAE,Scaffold,CC BY 4.0,"Lipophilicity measures the ability of a drug to dissolve in a lipid (e.g. fats, oils) environment. High lipophilicity often leads to high rate of metabolism, poor solubility, high turn-over, and low absorption. From MoleculeNet.","Regression. Given a drug SMILES string, predict the activity of lipophilicity.","AstraZeneca. Experimental in vitro Dmpk and physicochemical data on a set of publicly disclosed compounds (2016), Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,ADME,bbb_martins,2030,%,Binary,AUROC,Scaffold,CC BY 4.0,"As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system From MoleculeNet.","Binary classification. Given a drug SMILES string, predict the activity of BBB.","Martins, Ines Filipa, et al. ÒA Bayesian approach to in silico blood-brain barrier penetration modeling.Ó Journal of chemical information and modeling 52.6 (2012): 1686-1697., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,ADME,cyp3a4_substrate_carbonmangels,670,%,Binary,AUROC,Scaffold,CC BY 4.0,"CYP3A4 is an important enzyme in the body, mainly found in the liver and in the intestine. It oxidizes small foreign organic molecules (xenobiotics), such as toxins or drugs, so that they can be removed from the body. TDC used a dataset from [1], which merged information on substrates and nonsubstrates from six publications.","Binary Classification. Given a drug SMILES string, predict if it is a substrate to the enzyme.","Carbon_Mangels, Miriam, and Michael C. Hutter. ÒSelecting relevant descriptors for classification by bayesian estimates: a comparison with decision trees and support vector machines approaches for disparate data sets.Ó Molecular informatics 30.10 (2011): 885-895., Cheng, Feixiong, et al. ÒadmetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.Ó (2012): 3099-3105."
Single_instance_prediction,ADME,b3db_regression,942,,,,,CC0 1.0,"The Blood-Brain-Barrier Dataset (B3DB) is a curated resource of 7,807 small molecules classified as either BBB permeable (BBB+) or BBB non-permeable (BBB-), with 4,956 BBB+ and 2,851 BBB- molecules originally included. BBB permeability is measured by the logarithm of the brain-plasma concentration ratio:","Regression. Given a SMILES string, predict numerical logBB","Meng et al., A curated diverse molecular database of blood-brain barrier permeability with chemical descriptors, Scientific Data, vol. 8, Article 289, 2021."
Single_instance_prediction,ADME,hia_hou,578,%,Binary,AUROC,Scaffold,CC BY 4.0,"When a drug is orally administered, it needs to be absorbed from the human gastrointestinal system into the bloodstream of the human body. This ability of absorption is called human intestinal absorption (HIA) and it is crucial for a drug to be delivered to the target.","Binary classification. Given a drug SMILES string, predict the activity of HIA.",Hou T et al. ADME evaluation in drug discovery. 7. Prediction of oral absorption by correlation and classification. J Chem Inf Model. 2007;47(1):208-218.
Single_instance_prediction,ADME,cyp2d6_veith,13130,%,Binary,AUPRC,Scaffold,CC BY 4.0,"The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. Specifically, CYP2D6 is primarily expressed in the liver. It is also highly expressed in areas of the central nervous system, including the substantia nigra.","Binary Classification. Given a drug SMILES string, predict CYP2D6 inhibition.","Veith, Henrike et al. ÒComprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.Ó Nature biotechnology vol. 27,11 (2009): 1050-5."
Single_instance_prediction,ADME,solubility_aqsoldb,9980,log mol/L,Regression,MAE,Scaffold,CC BY 4.0,"Aqeuous solubility measures a drug's ability to dissolve in water. Poor water solubility could lead to slow drug absorptions, inadequate bioavailablity and even induce toxicity. More than 40% of new chemical entities are not soluble.","Regression. Given a drug SMILES string, predict the activity of solubility.","Sorkun, M.C., Khetan, A. & Er, S. AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds. Sci Data 6, 143 (2019)."
Single_instance_prediction,ADME,pampa_ncats,2034,,,,,CC BY 4.0,"PAMPA (parallel artificial membrane permeability assay) is a commonly employed assay to evaluate drug permeability across the cellular membrane. PAMPA is a non-cell-based, low-cost and high-throughput alternative to cellular models. Although PAMPA does not model active and efflux transporters, it still provides permeability values that are useful for absorption prediction because the majority of drugs are absorbed by passive diffusion through the membrane.","Binary classification. Given a compound's SMILES string, predict whether it is has high permeability (1) or low-to-moderate permeability (0) in PAMPA assay.","Siramshetty, V.B., Shah, P., et al. ÒValidating ADME QSAR Models Using Marketed Drugs.Ó SLAS Discovery 2021 Dec;26(10):1326-1336. doi: 10.1177/24725552211017520."
Single_instance_prediction,ADME,cyp3a4_veith,12328,%,Binary,AUPRC,Scaffold,CC BY 4.0,"The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. Specifically, CYP3A4 is an important enzyme in the body, mainly found in the liver and in the intestine. It oxidizes small foreign organic molecules (xenobiotics), such as toxins or drugs, so that they can be removed from the body.","Binary Classification. Given a drug SMILES string, predict CYP3A4 inhibition.","Veith, Henrike et al. ÒComprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.Ó Nature biotechnology vol. 27,11 (2009): 1050-5."
Single_instance_prediction,ADME,cyp2c9_substrate_carbonmangels,669,%,Binary,AUPRC,Scaffold,CC BY 4.0,"CYP P450 2C9 plays a major role in the oxidation of both xenobiotic and endogenous compounds. Substrates are drugs that are metabolized by the enzyme. TDC used a dataset from [1], which merged information on substrates and nonsubstrates from six publications.","Binary Classification. Given a drug SMILES string, predict if it is a substrate to the enzyme.","Carbon_Mangels, Miriam, and Michael C. Hutter. ÒSelecting relevant descriptors for classification by bayesian estimates: a comparison with decision trees and support vector machines approaches for disparate data sets.Ó Molecular informatics 30.10 (2011): 885-895., Cheng, Feixiong, et al. ÒadmetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.Ó (2012): 3099-3105."
Single_instance_prediction,ADME,half_life_obach,667,hr,Regression,Spearman,Scaffold,CC BY 4.0,Half life of a drug is the duration for the concentration of the drug in the body to be reduced by half. It measures the duration of actions of a drug. This dataset is from [1] and we obtain the deposited version under CHEMBL assay 1614674.,"Regression. Given a drug SMILES string, predict the half life duration.","Obach, R. Scott, Franco Lombardo, and Nigel J. Waters. ÒTrend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.Ó Drug Metabolism and Disposition 36.7 (2008): 1385-1405."
Single_instance_prediction,ADME,b3db_classification,6167,,,,,CC0 1.0,"The Blood-Brain-Barrier Dataset (B3DB) is a curated resource of 7,807 small molecules classified as either BBB permeable (BBB+) or BBB non-permeable (BBB-), with 4,956 BBB+ and 2,851 BBB- molecules originally included. BBB permeability is measured by the logarithm of the brain-plasma concentration ratio:","Binary classification. Given a compound's SMILES string, predict binary permeability label.","Meng et al., A curated diverse molecular database of blood-brain barrier permeability with chemical descriptors, Scientific Data, vol. 8, Article 289, 2021."
Single_instance_prediction,ADME,rlm,5590,,,,,Not specified,The metabolic stability of compounds in Human and Rat Liver Microsomes is a crucial parameter in early-stage drug development. ,"Binary classification. Given a drug SMILES string, predict the metabolic stability of the compound in Human and Rat Liver Microsomes.",
Single_instance_prediction,ADME,ppbr_az,1614,%,Regression,MAE,Scaffold,CC BY 4.0,"The human plasma protein binding rate (PPBR) is expressed as the percentage of a drug bound to plasma proteins in the blood. This rate strongly affect a drug's efficiency of delivery. The less bound a drug is, the more efficiently it can traverse and diffuse to the site of actions. From a ChEMBL assay deposited by AstraZeneca.","Regression. Given a drug SMILES string, predict the rate of PPBR.",AstraZeneca. Experimental in vitro Dmpk and physicochemical data on a set of publicly disclosed compounds (2016)
Single_instance_prediction,ADME,pgp_broccatelli,1218,%,Binary,AUROC,Scaffold,CC BY 4.0,"P-glycoprotein (Pgp) is an ABC transporter protein involved in intestinal absorption, drug metabolism, and brain penetration, and its inhibition can seriously alter a drug's bioavailability and safety. In addition, inhibitors of Pgp can be used to overcome multidrug resistance.","Binary classification. Given a drug SMILES string, predict the activity of Pgp inhibition.","Broccatelli et al., A Novel Approach for Predicting P-Glycoprotein (ABCB1) Inhibition Using Molecular Interaction Fields. Journal of Medicinal Chemistry, 2011 54 (6), 1740-1751"
Single_instance_prediction,ADME,caco2_wang,910,cm/s,Regression,MAE,Scaffold,CC BY 4.0,"The human colon epithelial cancer cell line, Caco-2, is used as an in vitro model to simulate the human intestinal tissue. The experimental result on the rate of drug passing through the Caco-2 cells can approximate the rate at which the drug permeates through the human intestinal tissue.","Regression. Given a drug SMILES string, predict the Caco-2 cell effective permeability.","Wang, NN et al, ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting, Journal of Chemical Information and Modeling 2016 56 (4), 763-773"
Single_instance_prediction,ADME,bioavailability_ma,640,%,Binary,AUROC,Scaffold,CC BY 4.0,Oral bioavailability is defined as Òthe rate and extent to which the active ingredient or active moiety is absorbed from a drug product and becomes available at the site of actionÓ.,"Binary classification. Given a drug SMILES string, predict the activity of bioavailability.","Ma, Chang-Ying, et al. ÒPrediction models of human plasma protein binding rate and oral bioavailability derived by using GAÐCGÐSVM method.Ó Journal of pharmaceutical and biomedical analysis 47.4-5 (2008): 677-682."
Single_instance_prediction,ADME,hydrationfreeenergy_freesolv,642,,,,,CC BY-NC-SA 4.0,"The Free Solvation Database, FreeSolv(SAMPL), provides experimental and calculated hydration free energy of small molecules in water. The calculated values are derived from alchemical free energy calculations using molecular dynamics simulations. From MoleculeNet.","Regression. Given a drug SMILES string, predict the activity of hydration free energy.","Mobley, David L., and J. Peter Guthrie. ÒFreeSolv: a database of experimental and calculated hydration free energies, with input files.Ó Journal of computer-aided molecular design 28.7 (2014): 711-720., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,ADME,cyp1a2_veith,12579,,,,,CC BY 4.0,"The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. Specifically, CYP1A2 localizes to the endoplasmic reticulum and its expression is induced by some polycyclic aromatic hydrocarbons (PAHs), some of which are found in cigarette smoke. It is able to metabolize some PAHs to carcinogenic intermediates. Other xenobiotic substrates for this enzyme include caffeine, aflatoxin B1, and acetaminophen.","Binary Classification. Given a drug SMILES string, predict CYP1A2 inhibition.","Veith, Henrike et al. ÒComprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.Ó Nature biotechnology vol. 27,11 (2009): 1050-5."
Single_instance_prediction,ADME,cyp2d6_substrate_carbonmangels,667,%,Binary,AUPRC,Scaffold,CC BY 4.0,"CYP2D6 is primarily expressed in the liver. It is also highly expressed in areas of the central nervous system, including the substantia nigra. TDC used a dataset from [1], which merged information on substrates and nonsubstrates from six publications.","Binary Classification. Given a drug SMILES string, predict if it is a substrate to the enzyme.","Carbon_Mangels, Miriam, and Michael C. Hutter. ÒSelecting relevant descriptors for classification by bayesian estimates: a comparison with decision trees and support vector machines approaches for disparate data sets.Ó Molecular informatics 30.10 (2011): 885-895., Cheng, Feixiong, et al. ÒadmetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.Ó (2012): 3099-3105."
Single_instance_prediction,ADME,approved_pampa_ncats,142,,,,,CC BY 4.0,"ÊPAMPA (parallel artificial membrane permeability assay) is a commonly employed assay to evaluate drug permeability across the cellular membrane. PAMPA is a non-cell-based, low-cost and high-throughput alternative to cellular models. Although PAMPA does not model active and efflux transporters, it still provides permeability values that are useful for absorption prediction because the majority of drugs are absorbed by passive diffusion through the membrane.","Binary classification. Given a compound's SMILES string, predict whether it is has high permeability (1) or low-to-moderate permeability (0) in PAMPA assay.","Siramshetty, V.B., Shah, P., et al. ÒValidating ADME QSAR Models Using Marketed Drugs.Ó SLAS Discovery 2021 Dec;26(10):1326-1336. doi: 10.1177/24725552211017520."
Single_instance_prediction,ADME,cyp2c9_veith,12092,%,Binary,AUPRC,Scaffold,CC BY 4.0,"The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. Specifically, the CYP P450 2C9 plays a major role in the oxidation of both xenobiotic and endogenous compounds.","Binary Classification. Given a drug SMILES string, predict CYP2C9 inhibition.","Veith, Henrike et al. ÒComprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.Ó Nature biotechnology vol. 27,11 (2009): 1050-5."
Single_instance_prediction,ADME,clearance_microsome_az,1102,mL.min-1.g-1,Regression,Spearman,Scaffold,CC BY 4.0,"Drug clearance is defined as the volume of plasma cleared of a drug over a specified time period and it measures the rate at which the active drug is removed from the body. This is a dataset curated from ChEMBL database containing experimental results on intrinsic clearance, deposited from AstraZeneca. It contains clearance measures from two experiments types, hepatocyte and microsomes. As many studies [2] have shown various clearance outcomes given these two different types, we separate them.","Regression. Given a drug SMILES string, predict the activity of clearance.","AstraZeneca. Experimental in vitro Dmpk and physicochemical data on a set of publicly disclosed compounds (2016), Di, Li, et al. ÒMechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design.Ó European journal of medicinal chemistry 57 (2012): 441-448."
Single_instance_prediction,Tox,toxcast_ATG_GATA_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_uPAR_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_TIMP2_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AP_2_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_Aromatase_Inhibition,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMass_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_HSE_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdoRA1,118,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hLTB4_BLT1,71,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rabI2C,106,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_FoxO_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_OHPROG_dn,500,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_StressKinase_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HIF1a_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_OTIC_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AP_2_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NCCT_HEK293T_CellTiterGLO,373,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_r5HT_NonSelective,92,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Antagonist_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NCCT_TPO_GUA_dn,53,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_HLADR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hCAR_Antagonist,277,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hDRD4.4,78,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hElastase,113,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hM1,83,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_IL8_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p4_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoticArrest_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_Antagonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_uPAR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_TGFb1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_HLADR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p4_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_p53_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rOpiate_NonSelectiveNa,122,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CAR_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_gDAT,173,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_Agonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p2_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP3A4_24hr,292,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_TR_LUC_GH3_Agonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_Eselectin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_Eselectin_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_E_Box_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_ESTRONE_up,502,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_LUC_MDAKB2_Antagonist2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_CD40_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_ESTRADIOL_dn,500,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GLI_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_LDLR_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPDE10,79,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PBREM_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_IL8_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AP_1_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_61_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_uPA_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NURR1_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_MCSF_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_antagonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_MIG_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hPXR,514,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_SR-ARE,5832,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_ATG_LXRa_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_LGIC_rNNR_BungSens,84,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p1_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_SULT2A_24hr,299,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hTXA2,95,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_uPAR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Myb_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Antagonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_Vis_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP3A4_6hr,296,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEK293_Media_blue,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_NFkB_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_TissueFactor_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPARg_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_h5HT2A,109,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_h5HT7,160,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HNF4a_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_32_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Antagonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hNK2,164,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_EGR_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Pax6_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP2,90,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_SR-ATAD5,7072,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_ANDR_dn,502,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_ESTRADIOL_up,500,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_gH2,120,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_Agonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_Antagonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_CFIN_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PXRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hES,161,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_NURR1_NURR1RXRa_1440,1737,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Myc_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hTrkA,63,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ESRE_BLA_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hPR,281,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdrb3,86,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP7,93,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_Eselectin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_AR_ARSRC1_0480,1740,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MicrotubuleCSK_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rTRH,942,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p1_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_AR_ARSRC1_0960,1733,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Sox_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p2_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NCCT_QuantiLum_inhib_2_dn,373,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEK293_Cell_blue,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP1,99,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Oct_MLP_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_EGFR_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_antagonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_DNADamage_48hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_E_Box_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_MMP_ratio_up,5271,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_uPAR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_SWIM_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Sox_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_AXIS_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ESRE_BLA_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TGFb_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_Thrombomodulin_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdra2C,112,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_gOpiateK,146,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HIF1a_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-ER-LBD,6955,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_ATG_M_32_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_06_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_h5HT6,100,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_Eotaxin3_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP2A6,113,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_oCOX1,140,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_PAI1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hFGFR1,165,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP3A4_48hr,294,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_Agonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_TRUN_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP19A1,239,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ARE_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP3A4,160,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NFI_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_FoxA2_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_11DCORT_dn,502,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_MIG_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_rSERT,113,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_HSE_BLA_agonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p5_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_MMP_viability,5271,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_antagonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NHEERL_ZF_144hpf_TERATOSCORE_up,703,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_CellLoss_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_PROG_up,469,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p3_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_agonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_p5HT2C,111,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hOpiate_D1,107,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_FXR_FXRSRC1_0480,1735,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_IL1a_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_VCAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_VCAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEPG2_Cell_blue,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_OR_gSIGMA_NonSelective,145,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ISRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_IP10_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_IL6_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_DOC_up,496,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_StressKinase_1h_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_JAW_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Myb_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_PAI1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Agonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_TR_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hAMPKa1,111,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_SREBP_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_DR5_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP1A1,175,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP13,82,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdoRA2a,86,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p3_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ACEA_T47D_80hr_Positive,1731,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_MCSF_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_Thrombomodulin_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_Proliferation_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_DOC_dn,496,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_VDRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RORb_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_IP10_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-AR-LBD,6758,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP2B6,136,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p4_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_MitoFxnI_24hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Agonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdrb2,78,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rNK1,112,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rV1,55,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RORg_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_uPAR_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_antagonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Xbp1_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_gMPeripheral_NonSelective,102,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_BRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMass_72h_dn,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_GSTA2_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_MMP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_Pselectin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_SAA_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_19_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GLI_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Antagonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_IL1a_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rMAOAP,106,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_MMP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP2B6_6hr,302,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TAL_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERRa_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A2_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CAR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_SNOU_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_SOMI_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARa_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_CellCycleArrest_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MicrotubuleCSK_72h_up,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,skin_reaction,404,,,,,CC BY 4.0,Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. The dataset used in this study was retrieved from the ICCVAM (Interagency Coordinating Committee on the Validation of Alternative Methods) report on the rLLNA.,"Binary classification. Given a drug SMILES string, predict whether it can cause skin reaction (1) or not (0).","Alves, Vinicius M., et al. ÒPredicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.Ó Toxicology and applied pharmacology 284.2 (2015): 262-272., The reduced murine local lymph node assay: an alternative test method using fewer animals to assess the allergic contact dermatitis potential of chemicals and products."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMass_72h_up,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_DNATexture_48hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPARa_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_oCOX2,103,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_Apoptosis_24hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_CellCycleArrest_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_Agonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_FXR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_IL6_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hRAR_Antagonist,260,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PXR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-AhR,6549,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rmAdra2B,103,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_Pselectin_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_VDR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_THRa1_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CMV_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_NFkB_BLA_agonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RORE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hAChE,142,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ELG1_LUC_Agonist,5271,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_IL8_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Antagonist_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMembPot_72h_dn,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERbERb_0480,1744,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hPPARa,376,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_SULT2A_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_antagonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_TissueFactor_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_NFkB_BLA_agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_p53Act_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_StressKinase_72h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hDRD2s,125,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NRF1_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Antagonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_VDR_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARa_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP9,97,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_IP10_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_ESTRONE_dn,502,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_CD69_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-Aromatase,5821,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_ATG_IR1_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERaERb_0480,1755,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_Thrombomodulin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TA_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_STAT3_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_IC_rCaBTZCHL,102,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_UGT1A1_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Agonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_p53Act_72h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_rCYP2C12,54,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GATA_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTPN12,79,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,herg_central_hERG_at_1uM,306893,,,,,CC BY 4.0,"Human ether-ˆ-go-go related gene (hERG) is crucial for the coordination of the heart's beating. Thus, if a drug blocks the hERG, it could lead to severe adverse effects. Therefore, reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. There are three targets: hERG_at_1uM, hERG_at_10uM, and hERG_inhib.","Regression. Given a drug SMILES string, predict the percent inhibition at a 1µM concentration.","Du F, Yu H, Zou B, Babcock J, Long S, Li M. hERGCentral: a large database to store, retrieve, and analyze compound-human Ether-ˆ-go-go related gene channel interactions to facilitate cardiotoxicity assessment in drug development. Assay Drug Dev Technol. 2011 Dec;9(6):580-8. doi: 10.1089/adt.2011.0425."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Agonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NFI_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_PBMCCytotoxicity_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hSIRT2,98,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hER,1128,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NCCT_TPO_AUR_dn,373,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_MP_rPBR,333,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_C_EBP_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_19_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hOpiate_mu,189,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NRF2_ARE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ARE_BLA_Agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_ICAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_LGIC_hNNR_NBungSens,50,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_THRa1_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A2_6hr,302,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_HSE_BLA_agonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_MitoFxnI_1hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEPG2_Media_blue,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Oct_MLP_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_SAA_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_bPR,185,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTPN9,108,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERRg_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_hNET,229,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_MIG_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_MIG_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_MCP1_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_CD38_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_MitoFxnI_48hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_mERa,928,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HNF4a_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_Agonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_TIMP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CMV_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_IC_rCaDHPRCh_L,89,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_IP10_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_TissueFactor_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_bAdoR_NonSelective,112,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_IL1a_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hM4,130,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rAdrb_NonSelective,65,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_XTT_Cytotoxicity_up,2893,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_NuclearSize_48hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_Proliferation_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hVEGFR2,154,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_MORT_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_bDR_NonSelective,55,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p3_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_VCAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_CellLoss_24hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-AR,7265,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_BSK_SAg_CD40_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GAL4_TRANS_dn,3144,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERbERb_1440,1666,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_antagonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_ABCB1_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_MMP_ratio_down,5271,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GR_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TAL_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rNK3,85,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP2D6,117,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_CellCycleArrest_72h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_NuclearSize_24hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hGSK3b,220,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p1_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_MRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rMAOAC,115,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_IR1_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_DR4_LXR_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_LXRb_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_hSERT,103,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Agonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_LUC_MDAKB2_Antagonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARb_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_VCAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p2_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HSE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_SR-MMP,5810,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_PE_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Agonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NURR1_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_Proliferation_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_Proliferation_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_MP_hPBR,348,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HNF6_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AR_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TCF_b_cat_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_GRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMembPot_1h_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_C_EBP_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Antagonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ESRE_BLA_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ACEA_T47D_80hr_Negative,1731,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_MCSF_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARg_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_MIG_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MicrotubuleCSK_72h_dn,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Ahr_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_NuclearSize_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_BRAI_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ARE_BLA_agonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_CRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEPG2_Media_green,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_uPA_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_PFIN_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,herg_karim,13445,,,,,CC BY 4.0,"A integrated Ether-a-go-go-related gene (hERG) dataset consisting of molecular structures labelled as hERG (<10uM) and non-hERG (>=10uM) blockers in the form of SMILES strings was obtained from the DeepHIT, the BindingDB database, ChEMBL bioactivity database, and other literature.","Binary classification. Given a drug SMILES string, predict whether it blocks (1, <10uM) or not blocks (0, >=10uM).",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_ATG_NF_kB_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_p53_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTEN,96,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_IL8_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_OxidativeStress_72h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Xbp1_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hBACE,170,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_uPAR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NCCT_QuantiLum_inhib_dn,318,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AhR_LUC_Agonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_DR5_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_CollagenIII_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hSIRT1,114,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_IC_hKhERGCh,91,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A2_24hr,302,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_VCAM1_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_NuclearSize_72h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_ICAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AutoFluor_HEPG2_Cell_green,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_NuclearSize_72h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_MMP1_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_MCSF_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_gLTB4,89,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTPN13,75,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hMMP3,104,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p4_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RXRa_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_FoxA2_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Ets_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPI3Ka,112,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_IL8_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_32_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rAdra1B,92,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_CIRC_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hM3,102,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_rMR,97,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NRF2_ARE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rCNOS,95,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMembPot_24h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERaERa_1440,1674,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPDE4A1,138,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERaERa_0480,1748,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_IC_rNaCh_site2,158,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_E2F_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_g5HT4,135,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_MCP1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_IL8_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARb_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdra2A,91,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hM2,118,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_32_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_MCP1_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_TNFa_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TGFb_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPDE5,180,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAT1,67,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_rAR,270,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hDUSP3,103,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_OHPREG_up,462,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hCK1D,130,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP2B6_24hr,299,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_OHPROG_up,500,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_TissueFactor_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hDRD1,130,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,herg_central_hERG_at_10uM,306893,,,,,CC BY 4.0,"Human ether-ˆ-go-go related gene (hERG) is crucial for the coordination of the heart's beating. Thus, if a drug blocks the hERG, it could lead to severe adverse effects. Therefore, reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. There are three targets: hERG_at_1uM, hERG_at_10uM, and hERG_inhib.","Regression. Given a drug SMILES string, predict the percent inhibition at a 10µM concentration.","Du F, Yu H, Zou B, Babcock J, Long S, Li M. hERGCentral: a large database to store, retrieve, and analyze compound-human Ether-ˆ-go-go related gene channel interactions to facilitate cardiotoxicity assessment in drug development. Assay Drug Dev Technol. 2011 Dec;9(6):580-8. doi: 10.1089/adt.2011.0425."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_TESTO_dn,500,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ISRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rAdra1_NonSelective,93,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_rVMAT2,102,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_Antagonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_h5HT5A,155,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_r5HT1_NonSelective,72,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-PPAR-gamma,6450,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p3_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,ld50_zhu,7385,log(1/(mol/kg)),Regression,MAE,Scaffold,CC BY 4.0,"Acute toxicity LD50 measures the most conservative dose that can lead to lethal adverse effects. The higher the dose, the more lethal of a drug.","Regression. Given a drug SMILES string, predict its acute toxicity.","Zhu, Hao, et al. ÒQuantitative structure_ activity relationship modeling of rat acute toxicity by oral exposure.Ó Chemical research in toxicology 22.12 (2009): 1913-1921."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rAChE,99,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Antagonist_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MicrotubuleCSK_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hFXR_Agonist,164,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rSST,70,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_AR_ARELUC_AG_1440,1772,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP1A2,173,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_IL1a_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ER_ERaERb_1440,1668,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RXRb_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RXRa_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rMAOBP,132,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_Steatosis_48hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERa_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_antagonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_EYE_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_LXRa_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hGR,345,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_TNFa_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_CellLoss_72h_dn,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RORg_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_DNATexture_24hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TA_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_NR-ER,6193,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hH1,90,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_ABCG2_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p1_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_CellLoss_48hr_dn,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_hDAT,243,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,herg_central_hERG_inhib,306893,%,Binary,AUROC,Scaffold,CC BY 4.0,"Human ether-ˆ-go-go related gene (hERG) is crucial for the coordination of the heart's beating. Thus, if a drug blocks the hERG, it could lead to severe adverse effects. Therefore, reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. There are three targets: hERG_at_1uM, hERG_at_10uM, and hERG_inhib.","Binary classification. Given a drug SMILES string, predict whether it blocks (1) or not blocks (0). This is equivalent to whether hERG_at_10uM < -50, i.e. whether the compound has an IC50 of less than 10µM.","Du F, Yu H, Zou B, Babcock J, Long S, Li M. hERGCentral: a large database to store, retrieve, and analyze compound-human Ether-ˆ-go-go related gene channel interactions to facilitate cardiotoxicity assessment in drug development. Assay Drug Dev Technol. 2011 Dec;9(6):580-8. doi: 10.1089/adt.2011.0425."
Single_instance_prediction,Tox,toxcast_ATG_LXRb_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_agonist_ratio,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_tPA_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_Eselectin_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_ActivityScore,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RARg_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_FoxO_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_cAR,304,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_hAdoT,77,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_BRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p5_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Antagonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,herg,655,%,Binary,AUROC,Scaffold,CC BY 4.0,"Human ether-ˆ-go-go related gene (hERG) is crucial for the coordination of the heart's beating. Thus, if a drug blocks the hERG, it could lead to severe adverse effects. Therefore, reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages.","Binary classification. Given a drug SMILES string, predict whether it blocks (1) or not blocks (0).","Wang, Shuangquan, et al. ÒADMET evaluation in drug discovery. 16. Predicting hERG blockers by combining multiple pharmacophores and machine learning approaches.Ó Molecular Pharmaceutics 13.8 (2016): 2855-2866."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A1_24hr,296,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_TissueFactor_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rAdra2_NonSelective,78,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_Thrombomodulin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_SR-HSE,6467,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,dili,475,%,Binary,AUROC,Scaffold,CC BY 4.0,"Drug-induced liver injury (DILI) is fatal liver disease caused by drugs and it has been the single most frequent cause of safety-related drug marketing withdrawals for the past 50 years (e.g. iproniazid, ticrynafen, benoxaprofen). This dataset is aggregated from U.S. FDAÕs National Center for Toxicological Research.","Binary classification. Given a drug SMILES string, predict whether it can cause liver injury (1) or not (0).","Xu, Youjun, et al. ÒDeep learning for drug-induced liver injury.Ó Journal of chemical information and modeling 55.10 (2015): 2085-2093."
Single_instance_prediction,Tox,toxcast_BSK_LPS_PGE2_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_TR_LUC_GH3_Antagonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_FXR_BLA_agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_LUC_MDAKB2_Agonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_FXR_FXRSRC1_1440,1682,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_VDRE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Antagonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_TR_rNET,78,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_bER,1054,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP2C9,225,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,clintox,1478,,,,,CC BY 4.0,The ClinTox dataset includes drugs that have failed clinical trials for toxicity reasons and also drugs that are associated with successful trials.,"Binary classification. Given a drug SMILES string, predict the clinical toxicity.","Gayvert, Kaitlyn M., Neel S. Madhukar, and Olivier Elemento. ÒA data-driven approach to predicting successes and failures of clinical trials.Ó Cell chemical biology 23.10 (2016): 1294-1301."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_Antagonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_OxidativeStress_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPARd_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_ERRg_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTPRC,67,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_LUC_BG1_Agonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_IL8_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_TGFb1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Myc_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Agonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_PIG_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rOpiate_NonSelective,129,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_LPS_PGE2_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Ets_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_rMAOBC,128,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_Tanguay_ZF_120hpf_YSE_up,1021,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_LGIC_h5HT3,66,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hAurA,95,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Ahr_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoticArrest_72h_up,1019,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RORE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARd_BLA_Antagonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hFXR_Antagonist,257,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_Proliferation_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_NFkB_BLA_agonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PPARa_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_RXRb_TRANS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_TCF_b_cat_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP4F12,77,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_SREBP_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CEETOX_H295R_CORTISOL_dn,502,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_LGIC_bGABARa1,67,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_AR_BLA_Antagonist_viability,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_E2F_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PXRE_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_gLTD4,65,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hTRa_Antagonist,223,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_AP_1_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_DR4_LXR_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_STAT3_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_LUC_BG1_Antagonist,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_GR_BLA_Agonist_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A1_6hr,302,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p5_ch2,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hPPARg,780,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ARE_BLA_Agonist_ch1,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p5_ratio,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Sp1_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ESRE_BLA_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_hAdrb1,95,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_MMP1_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ERa_EREGFP_0480,1758,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_KF3CT_MMP9_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_Sp1_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_GPCR_rabPAF,99,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,carcinogens_lagunin,280,,,,,CC BY 4.0,"A carcinogen is any substance, radionuclide, or radiation that promotes carcinogenesis, the formation of cancer. This may be due to the ability to damage the genome or to the disruption of cellular metabolic processes.","Binary classification. Given a drug SMILES string, predict whether it can cause carcinogen.","Lagunin, Alexey, et al. ÒComputer_aided prediction of rodent carcinogenicity by PASS and CISOC_PSCT.Ó QSAR & Combinatorial Science 28.8 (2009): 806-810., Cheng, Feixiong, et al. ÒadmetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.Ó (2012): 3099-3105."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hAR,228,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ADME_hCYP2C19,377,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_LGIC_rGABAR_NonSelective,62,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_LDLR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_NR_hRARa_Agonist,166,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_BE3C_uPAR_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_Eselectin_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_3C_VCAM1_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_Apoptosis_48hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_NURR1_NURR1RXRa_0480,1758,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_CASM3C_HLADR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_PPARg_BLA_antagonist_viability,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_Steatosis_24hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_hDFCGF_EGFR_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PBREM_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,tox21_SR-p53,6774,,,,,CC BY 4.0,"Tox21 is a data challenge which contains qualitative toxicity measurements for 7,831 compounds on 12 different targets, such as nuclear receptors and stree response pathways.","Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.",Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs
Single_instance_prediction,Tox,toxcast_BSK_SAg_PBMCCytotoxicity_up,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_M_19_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_UGT1A1_24hr,302,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NF_kB_CIS_up,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_PXR_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HNF6_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_VDR_BLA_agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hCASP5,79,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_Hepat_DNADamage_24hr_up,303,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_NVS_ENZ_hPTPN11,87,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_ERa_BLA_Agonist_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_OT_ERa_EREGFP_0120,1771,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,ames,7278,%,Binary,AUROC,Scaffold,CC BY 4.0,"Mutagenicity means the ability of a drug to induce genetic alterations. Drugs that can cause damage to the DNA can result in cell death or other severe adverse effects. Nowadays, the most widely used assay for testing the mutagenicity of compounds is the Ames experiment which was invented by a professor named Ames. The Ames test is a short-term bacterial reverse mutation assay detecting a large number of compounds which can induce genetic damage and frameshift mutations. The dataset is aggregated from four papers.","Binary classification. Given a drug SMILES string, predict whether it is mutagenic (1) or not mutagenic (0).","Xu, Congying, et al. ÒIn silico prediction of chemical Ames mutagenicity.Ó Journal of chemical information and modeling 52.11 (2012): 2840-2847."
Single_instance_prediction,Tox,toxcast_ATG_GR_TRANS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_HSE_BLA_agonist_ch2,7187,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_TOX21_p53_BLA_p2_ch1,7931,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP2B6_48hr,300,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_CLD_CYP1A1_48hr,295,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_SAg_SRB_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_BSK_4H_VEGFRII_down,1439,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_APR_HepG2_MitoMass_24h_up,1034,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_HSE_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,Tox,toxcast_ATG_NRF1_CIS_dn,3412,,,,,CC BY 4.0,ToxCast includes qualitative results of over 600 experiments on 8k compounds.,"Binary classification. Given a drug SMILES string, predict the toxicity in a specific assay.","Richard, Ann M., et al. ÒToxCast chemical landscape: paving the road to 21st century toxicology.Ó Chemical research in toxicology 29.8 (2016): 1225-1251."
Single_instance_prediction,HTS,m1_muscarinic_receptor_antagonists_butkiewicz,61748,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,choline_transporter_butkiewicz,302235,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,cav3_t-type_calcium_channels_butkiewicz,100858,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,potassium_ion_channel_kir2.1_butkiewicz,301424,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,tyrosyl-dna_phosphodiesterase_butkiewicz,341312,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,kcnq2_potassium_channel_butkiewicz,302336,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,sarscov2_3clpro_diamond,880,,,,,CC BY 4.0,A large XChem crystallographic fragment screen against SARS-CoV-2 main protease at high resolution. From MIT AiCures.,"Binary classification. Given a drug SMILES string, predict its activity against SARSCoV2 3CL Protease.","Diamond Light Source, MIT AI Cures."
Single_instance_prediction,HTS,hiv,41124,,,,,CC BY 4.0,"The HIV dataset was introduced by the Drug Therapeutics Program (DTP) AIDS Antiviral Screen, which tested the ability to inhibit HIV replication for over 40,000 compounds. From MoleculeNet.","Binary classification. Given a drug SMILES string, predict its activity against HIV virus.","AIDS Antiviral Screen Data., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,HTS,sarscov2_vitro_touret,1484,,,,,CC BY 4.0,"An in-vitro screen of the Prestwick chemical library composed of 1,480 approved drugs in an infected cell-based assay. From MIT AiCures.","Binary classification. Given a drug SMILES string, predict its activity against SARSCoV2.","Touret, F., Gilles, M., Barral, K. et al. In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication. Sci Rep 10, 13093 (2020)., MIT AI Cures."
Single_instance_prediction,HTS,m1_muscarinic_receptor_agonists_butkiewicz,61825,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,orexin1_receptor_butkiewicz,218105,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,HTS,serine_threonine_kinase_33_butkiewicz,319721,,,,,CC BY 4.0,"These are nine high-quality high-throughput screening (HTS) datasets from [1]. These datasets were curated from HTS data at the PubChem database [2]. Typically, HTS categorizes small molecules into hit, inactive, or unspecified against a certain therapeutic target. However, a compound may be falsely classified as a hit due to experimental artifacts such as optical interference. Moreover, because the screening is performed without duplicates, and the cutoff is often set loose to minimize the false negative rates, the results from the primary screens often contain high false positive rates [3]. Hence the result from the primary screen is only used as the first iteration to reduce the compound library to a smaller set of further confirmatory tests. Here each dataset is carefully collated through confirmation screens to validate active compounds. The curation process is documented in [1]. Each dataset is identified by the PubChem Assay ID (AID). Features of the datasets: (1) At least 150 confirmed active compounds present; (2) Diverse target classes; (3) Realistic (large number and highly imbalanced label).","Binary classification. Given a compound SMILES string, predict its activity against a diverse set of targets.","Butkiewicz, Mariusz, et al. ÒBenchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Ó Molecules 18.1 (2013): 735-756., Kim, Sunghwan, et al. ÒPubChem 2019 update: improved access to chemical data.Ó Nucleic acids research 47.D1 (2019): D1102-D1109., Butkiewicz, Mariusz, et al. ÒHigh-throughput screening assay datasets from the pubchem database.Ó Chemical informatics (Wilmington, Del.) 3.1 (2017)."
Single_instance_prediction,QM,qm9_lumo,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_E2-CAM,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_zpve,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_Cv,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_homo,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_E2-CC2,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_f2-CC2,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_IMAX_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm9_alpha,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_G,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_AE_PBE0,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm8_f1-CC2,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_P_SCS,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm9_A,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_f2-PBE0,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_P_PBE0,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_LUMO_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm9_H,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_U,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_U0,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_E1_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_IP_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_LUMO_PBE0,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm8_E1-CC2,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_HOMO_PBE0,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm8_E1-CAM,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_C,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_f1-CAM,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_E2-PBE0,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_E1-PBE0,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,"Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_mu,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm7b_EA_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_EMAX_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_HOMO_GW,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_HOMO_ZINDO,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm7b_LUMO_GW,111180,,,,,CC BY 4.0,"QM7 is a subset of GDB-13 (a database of nearly 1 billion stable and synthetically accessible organic molecules) composed of all molecules of up to 23 atoms (including 7 heavy atoms C, N, O, and S), where 14 properties (e.g. polarizability, HOMO and LUMO eigenvalues, excitation energies) have to be predicted at different levels of theory (ZINDO, SCS, PBE0, GW).","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Blum, Lorenz C., and Jean-Louis Reymond. Ò970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.Ó Journal of the American Chemical Society 131.25 (2009): 8732-8733., Montavon, GrŽgoire, et al. ÒMachine learning of molecular electronic properties in chemical compound space.Ó New Journal of Physics 15.9 (2013): 095003."
Single_instance_prediction,QM,qm9_B,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_gap,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm9_r2,2407753,,,,,CC BY 4.0,"computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. From MoleculeNet and loaded from DeepChem.","Regression. Given a drug 3D xyz coordinates, predict the drug property.","Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,QM,qm8_f1-PBE0,349970,,,,,CC BY 4.0,Electronic spectra and excited state energy of small molecules calculated by multiple quantum mechanic methods. Consisting of low-lying singlet-singlet vertical electronic spectra of over 20_000 synthetically feasible small organic molecules with up to eight CONF atom. From MoleculeNet and loaded from DeepChem.,,"Ruddigkeit, Lars, et al. ÒEnumeration of 166 billion organic small molecules in the chemical universe database GDB-17.Ó Journal of chemical information and modeling 52.11 (2012): 2864-2875., Ramakrishnan, Raghunathan, et al. ÒElectronic spectra from TDDFT and machine learning in chemical space.Ó The Journal of chemical physics 143.8 (2015): 084111., Ramsundar, Bharath, et al. Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more. Ò OÕReilly Media, Inc.Ó, 2019., Wu, Zhenqin, et al. ÒMoleculeNet: a benchmark for molecular machine learning.Ó Chemical science 9.2 (2018): 513-530."
Single_instance_prediction,Epitope,iedb_jespersen,3159,,,,,CC BY 4.0,"Epitope prediction is to predict the active region in the antigen. This dataset is from Bepipred, which curates a dataset from IEDB. It collects B-cell epitopes and non-epitope amino acids determined from crystal structures.","Token-level classification. Given an amino acid sequence, predict amino acid token that is active in binding, i.e. X is amino acid sequence, Y is a list of indices for the active positions in X.","Vita, Randi, et al. ÒThe immune epitope database (IEDB): 2018 update.Ó Nucleic acids research 47.D1 (2019): D339-D343., Jespersen, Martin Closter, et al. ÒBepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes.Ó Nucleic acids research 45.W1 (2017): W24-W29."
Single_instance_prediction,Epitope,pdb_jespersen,447,,,,,CC BY 4.0,"Epitope prediction is to predict the active region in the antigen. This dataset is from Bepipred, which curates a dataset from PDB. It collects B-cell epitopes and non-epitope amino acids determined from crystal structures.","Token-level classification. Given the antigen's amino acid sequence, predict amino acid token that is active in binding, i.e. X is an amino acid sequence, Y is a list of indices for the active tokens in X.","Jespersen, Martin Closter, et al. ÒBepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes.Ó Nucleic acids research 45.W1 (2017): W24-W29., Berman, Helen M., et al. ÒThe protein data bank.Ó Nucleic acids research 28.1 (2000): 235-242."
Single_instance_prediction,Develop,tap_CDR_Length,241,,,,,CC BY 4.0,"Immunogenicity, instability, self-association, high viscosity, polyspecificity, or poor expression can all preclude an antibody from becoming a therapeutic. Early identification of these negative characteristics is essential. Akin to the Lipinski guidelines, which measure druglikeness in small molecules, Therapeutic Antibody Profiler (TAP) highlights antibodies that possess characteristics that are rare/unseen in clinical-stage mAb therapeutics. In this dataset, TDC includes five metrics measuring developability of an antibody: CDR length, patches of surface hydrophobicity (PSH), patches of positive charge (PPC), patches of negative charge (PNC), structural Fv charge symmetry parameter (SFvCSP).","Regression. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Raybould, Matthew IJ, et al. ÒFive computational developability guidelines for therapeutic antibody profiling.Ó Proceedings of the National Academy of Sciences 116.10 (2019): 4025-4030."
Single_instance_prediction,Develop,sabdab_chen,2409,,,,,CC BY 3.0,"Antibody data from Chen et al, where they process from the SAbDab. From an initial dataset of 3816 antibodies, they retained 2426 antibodies that satisfy the following criteria: 1. have both sequence (FASTA) and Protein Data Bank (PDB) structure files, 2. contain both a heavy chain and a light chain, and 3. have crystal structures with resolution < 3 . The DI label is derived from BIOVIA's pipelines.","Binary classification. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Chen, Xingyao, et al. ÒPredicting antibody developability from sequence using machine learning.Ó bioRxiv (2020)., Dunbar, James, et al. ÒSAbDab: the structural antibody database.Ó Nucleic acids research 42.D1 (2014): D1140-D1146., Biovia, Dassault Systmes. ÒBIOVIA pipeline pilot.Ó Dassault Systmes: San Diego, BW, Release (2017)."
Single_instance_prediction,Develop,tap_SFvCSP,241,,,,,CC BY 4.0,"Immunogenicity, instability, self-association, high viscosity, polyspecificity, or poor expression can all preclude an antibody from becoming a therapeutic. Early identification of these negative characteristics is essential. Akin to the Lipinski guidelines, which measure druglikeness in small molecules, Therapeutic Antibody Profiler (TAP) highlights antibodies that possess characteristics that are rare/unseen in clinical-stage mAb therapeutics. In this dataset, TDC includes five metrics measuring developability of an antibody: CDR length, patches of surface hydrophobicity (PSH), patches of positive charge (PPC), patches of negative charge (PNC), structural Fv charge symmetry parameter (SFvCSP).","Regression. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Raybould, Matthew IJ, et al. ÒFive computational developability guidelines for therapeutic antibody profiling.Ó Proceedings of the National Academy of Sciences 116.10 (2019): 4025-4030."
Single_instance_prediction,Develop,tap_PNC,241,,,,,CC BY 4.0,"Immunogenicity, instability, self-association, high viscosity, polyspecificity, or poor expression can all preclude an antibody from becoming a therapeutic. Early identification of these negative characteristics is essential. Akin to the Lipinski guidelines, which measure druglikeness in small molecules, Therapeutic Antibody Profiler (TAP) highlights antibodies that possess characteristics that are rare/unseen in clinical-stage mAb therapeutics. In this dataset, TDC includes five metrics measuring developability of an antibody: CDR length, patches of surface hydrophobicity (PSH), patches of positive charge (PPC), patches of negative charge (PNC), structural Fv charge symmetry parameter (SFvCSP).","Regression. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Raybould, Matthew IJ, et al. ÒFive computational developability guidelines for therapeutic antibody profiling.Ó Proceedings of the National Academy of Sciences 116.10 (2019): 4025-4030."
Single_instance_prediction,Develop,tap_PSH,241,,,,,CC BY 4.0,"Immunogenicity, instability, self-association, high viscosity, polyspecificity, or poor expression can all preclude an antibody from becoming a therapeutic. Early identification of these negative characteristics is essential. Akin to the Lipinski guidelines, which measure druglikeness in small molecules, Therapeutic Antibody Profiler (TAP) highlights antibodies that possess characteristics that are rare/unseen in clinical-stage mAb therapeutics. In this dataset, TDC includes five metrics measuring developability of an antibody: CDR length, patches of surface hydrophobicity (PSH), patches of positive charge (PPC), patches of negative charge (PNC), structural Fv charge symmetry parameter (SFvCSP).","Regression. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Raybould, Matthew IJ, et al. ÒFive computational developability guidelines for therapeutic antibody profiling.Ó Proceedings of the National Academy of Sciences 116.10 (2019): 4025-4030."
Single_instance_prediction,Develop,tap_PPC,241,,,,,CC BY 4.0,"Immunogenicity, instability, self-association, high viscosity, polyspecificity, or poor expression can all preclude an antibody from becoming a therapeutic. Early identification of these negative characteristics is essential. Akin to the Lipinski guidelines, which measure druglikeness in small molecules, Therapeutic Antibody Profiler (TAP) highlights antibodies that possess characteristics that are rare/unseen in clinical-stage mAb therapeutics. In this dataset, TDC includes five metrics measuring developability of an antibody: CDR length, patches of surface hydrophobicity (PSH), patches of positive charge (PPC), patches of negative charge (PNC), structural Fv charge symmetry parameter (SFvCSP).","Regression. Given the antibody's heavy chain and light chain sequence, predict its developability. The input X is a list of two sequences where the first is the heavy chain and the second light chain.","Raybould, Matthew IJ, et al. ÒFive computational developability guidelines for therapeutic antibody profiling.Ó Proceedings of the National Academy of Sciences 116.10 (2019): 4025-4030."
Single_instance_prediction,CRISPROutcome,leenay_Indel_Diversity,1521,,,,,CC BY 3.0,"Primary T cells are a promising cell type for therapeutic genome editing, as they can be engineered efficiently ex vivo and transferred to patients. This dataset consists of the DNA repair outcomes of CRISPR-CAS9 knockout experiments on primary CD4+ T cells drawn from 15 donors. For each of the 1,521 unique genomic locations from 553 genes, we provide the 20-nucleotide guide sequence along with the 3-nucletoide PAM sequence.","Regression. Given a DNA sequence, predict the repair outcomes of a CRISPR-CAS9 knockout experiment.","Leenay, Ryan T., et al. ÒLarge dataset enables prediction of repair after CRISPRÐCas9 editing in primary T cells.Ó Nature biotechnology 37.9 (2019): 1034-1037."
Single_instance_prediction,CRISPROutcome,leenay_Fraction_Frameshifts,1521,,,,,CC BY 3.0,"Primary T cells are a promising cell type for therapeutic genome editing, as they can be engineered efficiently ex vivo and transferred to patients. This dataset consists of the DNA repair outcomes of CRISPR-CAS9 knockout experiments on primary CD4+ T cells drawn from 15 donors. For each of the 1,521 unique genomic locations from 553 genes, we provide the 20-nucleotide guide sequence along with the 3-nucletoide PAM sequence.","Regression. Given a DNA sequence, predict the repair outcomes of a CRISPR-CAS9 knockout experiment.","Leenay, Ryan T., et al. ÒLarge dataset enables prediction of repair after CRISPRÐCas9 editing in primary T cells.Ó Nature biotechnology 37.9 (2019): 1034-1037."
Single_instance_prediction,CRISPROutcome,leenay_Avg_Deletion_Length,1521,,,,,CC BY 3.0,"Primary T cells are a promising cell type for therapeutic genome editing, as they can be engineered efficiently ex vivo and transferred to patients. This dataset consists of the DNA repair outcomes of CRISPR-CAS9 knockout experiments on primary CD4+ T cells drawn from 15 donors. For each of the 1,521 unique genomic locations from 553 genes, we provide the 20-nucleotide guide sequence along with the 3-nucletoide PAM sequence.","Regression. Given a DNA sequence, predict the repair outcomes of a CRISPR-CAS9 knockout experiment.","Leenay, Ryan T., et al. ÒLarge dataset enables prediction of repair after CRISPRÐCas9 editing in primary T cells.Ó Nature biotechnology 37.9 (2019): 1034-1037."
Single_instance_prediction,CRISPROutcome,leenay_Fraction_Insertions,1521,,,,,CC BY 3.0,"Primary T cells are a promising cell type for therapeutic genome editing, as they can be engineered efficiently ex vivo and transferred to patients. This dataset consists of the DNA repair outcomes of CRISPR-CAS9 knockout experiments on primary CD4+ T cells drawn from 15 donors. For each of the 1,521 unique genomic locations from 553 genes, we provide the 20-nucleotide guide sequence along with the 3-nucletoide PAM sequence.","Regression. Given a DNA sequence, predict the repair outcomes of a CRISPR-CAS9 knockout experiment.","Leenay, Ryan T., et al. ÒLarge dataset enables prediction of repair after CRISPRÐCas9 editing in primary T cells.Ó Nature biotechnology 37.9 (2019): 1034-1037."
Single_instance_prediction,CRISPROutcome,leenay_Avg_Insertion_Length,1521,,,,,CC BY 3.0,"Primary T cells are a promising cell type for therapeutic genome editing, as they can be engineered efficiently ex vivo and transferred to patients. This dataset consists of the DNA repair outcomes of CRISPR-CAS9 knockout experiments on primary CD4+ T cells drawn from 15 donors. For each of the 1,521 unique genomic locations from 553 genes, we provide the 20-nucleotide guide sequence along with the 3-nucletoide PAM sequence.","Regression. Given a DNA sequence, predict the repair outcomes of a CRISPR-CAS9 knockout experiment.","Leenay, Ryan T., et al. ÒLarge dataset enables prediction of repair after CRISPRÐCas9 editing in primary T cells.Ó Nature biotechnology 37.9 (2019): 1034-1037."