P
Philip E. Bourne
Researcher at University of Virginia
Publications - 357
Citations - 64294
Philip E. Bourne is an academic researcher from University of Virginia. The author has contributed to research in topics: Protein Data Bank & Structural genomics. The author has an hindex of 68, co-authored 331 publications receiving 54563 citations. Previous affiliations of Philip E. Bourne include University of Sheffield & University of California, Los Angeles.
Papers
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Book ChapterDOI
CASP and CAFASP experiments and their findings
TL;DR: This short introductory chapter is intended simply to introduce a sense of the progress, limitations, challenges, and likely future developments in the field of protein structure prediction through what seems to be a unique scientific process.
Journal ArticleDOI
Peptide Identification by Database Search of Mixture Tandem Mass Spectra
TL;DR: This work proposes a new database search tool (MixDB) that is able to identify mixture tandem mass spectra from more than one peptide, and shows that peptides can be reliably identified with up to 95% accuracy from mixture spectra.
Journal ArticleDOI
Toward effective software solutions for big biology
Pjotr Prins,Joep de Ligt,Artem V. Tarasov,Ritsert C. Jansen,Edwin Cuppen,Edwin Cuppen,Philip E. Bourne +6 more
TL;DR: A bioinformatics manifesto is published as a practical guide for FOSS-style development that aims to provide process and architecture guidelines for early-career bioinformaticians and their supervisors.
Book ChapterDOI
The immune epitope database and analysis resource
Alessandro Sette,Huynh-Hoa Bui,John Sidney,Philip E. Bourne,Søren Buus,Ward Fleri,Ralph T. Kubo,Ole Lund,David Nemazee,Julia Ponomarenko,Muthuraman Sathiamurthy,Stephani Stewart,Scott Way,Stephen S. Wilson,Bjoern Peters +14 more
TL;DR: The utility of the IEDB was recently demonstrated through a comprehensive analysis of all current information regarding antibody and T cell epitopes derived from influenza A and determining possible cross-reactivity among H5N1 avian flu and human flu viruses.
Journal ArticleDOI
Insights into the binding mode of MEK type-III inhibitors. A step towards discovering and designing allosteric kinase inhibitors across the human kinome
TL;DR: This work systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation, and hypothesize that the helix-folding activation loop is a hallmark allosteric binding site for type- III inhibitors.