Philip E. Bourne

TL;DR: This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine and has important implications for drug development and personalized medicine.

TL;DR: A comparison tool for calculating both 1D protein sequence and 3D protein structure alignments and allows users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user.

TL;DR: This work consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model.

TL;DR: This paper shows how the use of support vector machines (SVMs), trained by associating sets of individual energy terms retrieved from molecular docking with the known binding affinity of each compound from high-throughput screening experiments, can be used to improve the correlation between known binding affinities and those predicted by the docking program eHiTS.

TL;DR: A web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins, is developed.