Machine learning in drug discovery and development

Bioinformatics challenges for genome-wide association studies

(2010) J. H. Moore et al.   BIOINFORMATICS

Ranking Chemical Structures for Drug Discovery: A New Machine Learning Approach

(2010) Shivani Agarwal et al.   Journal of Chemical Information and Modeling

The use of machine learning and nonlinear statistical tools for ADME prediction

(2009) Yojiro Sakiyama   Expert Opinion on Drug Metabolism & Toxicology

Exploring Potency and Selectivity Receptor Antagonist Profiles Using a Multilabel Classification Approach: The Human Adenosine Receptors as a Key Study

(2009) Lisa Michielan et al.   Journal of Chemical Information and Modeling

Target Fishing for Chemical Compounds Using Target-Ligand Activity Data and Ranking Based Methods

(2009) Nikil Wale et al.   Journal of Chemical Information and Modeling

Searching for Target-Selective Compounds Using Different Combinations of Multiclass Support Vector Machine Ranking Methods, Kernel Functions, and Fingerprint Descriptors

(2009) Anne Mai Wassermann et al.   Journal of Chemical Information and Modeling

Predicting promiscuity

(2009) Andrew L. Hopkins   NATURE

In silico toxicology for the pharmaceutical sciences☆

(2009) Luis G. Valerio Jr.   TOXICOLOGY AND APPLIED PHARMACOLOGY

Prediction of drug-target interaction networks from the integration of chemical and genomic spaces

(2008) Y. Yamanishi et al.   BIOINFORMATICS

Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds

(2008) Hanna Geppert et al.   Journal of Chemical Information and Modeling

Network pharmacology: the next paradigm in drug discovery

(2008) Andrew L Hopkins   Nature Chemical Biology