Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set

Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric

(2017) Sabri Boughorbel et al.   PLoS One

Assessing the Growth of Bioactive Compounds and Scaffolds over Time: Implications for Lead Discovery and Scaffold Hopping

(2016) Swarit Jasial et al.   Journal of Chemical Information and Modeling

Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound–Kinase Activities: A Way toward Selective Promiscuity by Design?

(2016) Serge Christmann-Franck et al.   Journal of Chemical Information and Modeling

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Multitask learning improves prediction of cancer drug sensitivity

(2016) Han Yuan et al.   Scientific Reports

Deep Learning for Drug-Induced Liver Injury

(2015) Youjun Xu et al.   Journal of Chemical Information and Modeling

Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

(2015) Junshui Ma et al.   Journal of Chemical Information and Modeling

Activity, assay and target data curation and quality in the ChEMBL database

(2015) George Papadatos et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Deep learning

(2015) Yann LeCun et al.   NATURE

Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects

(2015) Isidro Cortés-Ciriano et al.   MedChemComm

Accurate and efficient target prediction using a potency-sensitive influence-relevance voter

(2015) Alessandro Lusci et al.   Journal of Cheminformatics

A multi-label approach to target prediction taking ligand promiscuity into account

(2015) Avid M Afzal et al.   Journal of Cheminformatics

Target prediction utilising negative bioactivity data covering large chemical space

(2015) Lewis H. Mervin et al.   Journal of Cheminformatics

Mycobacterial Dihydrofolate Reductase Inhibitors Identified Using Chemogenomic Methods and In Vitro Validation

(2015) Grace Mugumbate et al.   PLoS One

Chemical, Target, and Bioactive Properties of Allosteric Modulation

(2014) Gerard J. P. van Westen et al.   PLoS Computational Biology

Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules

(2013) Alessandro Lusci et al.   Journal of Chemical Information and Modeling

Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.

(2013) Robert P. Sheridan   Journal of Chemical Information and Modeling

The ChEMBL bioactivity database: an update

(2013) A. Patrícia Bento et al.   NUCLEIC ACIDS RESEARCH

Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets

(2013) Gerard JP van Westen et al.   Journal of Cheminformatics

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

(2013) Gerard JP van Westen et al.   Journal of Cheminformatics

Growth of Ligand–Target Interaction Data in ChEMBL Is Associated with Increasing and Activity Measurement-Dependent Compound Promiscuity

(2012) Ye Hu et al.   Journal of Chemical Information and Modeling

The Experimental Uncertainty of Heterogeneous Public Ki Data

(2012) Christian Kramer et al.   JOURNAL OF MEDICINAL CHEMISTRY

ChEMBL: a large-scale bioactivity database for drug discovery

(2011) A. Gaulton et al.   NUCLEIC ACIDS RESEARCH

Proteochemometric modeling as a tool to design selective compounds and for extrapolating to novel targets

(2010) Gerard J. P. van Westen et al.   MedChemComm

Influence Relevance Voting: An Accurate And Interpretable Virtual High Throughput Screening Method

(2009) S. Joshua Swamidass et al.   Journal of Chemical Information and Modeling

Virtual screening of GPCRs: An in silico chemogenomics approach

(2008) Laurent Jacob et al.   BMC BIOINFORMATICS