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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Journal ArticleDOI
Con-Struct Map
TL;DR: This paper presents a graphical tool for the comparative study of protein structures that detects potential conserved residue contacts shared by multiple protein structures by superimposing their contact maps according to a multiple structure alignment.
Journal ArticleDOI
High-throughput identification of interacting protein-protein binding sites
TL;DR: A new method using a machine learning approach to detect if protein binding sites, once identified, interact with each other and is capable of identifying binding sites for proteins, their interacting binding sites and, ultimately, their binding partners on a large scale.
Peer ReviewDOI
Author response: How open science helps researchers succeed
Erin C. McKiernan,Philip E. Bourne,C. Titus Brown,Stuart Buck,Amye Kenall,Jennifer Lin,Damon McDougall,Brian A. Nosek,Karthik Ram,Courtney K. Soderberg,Jeffrey R. Spies,Jeffrey R. Spies,Kaitlin Thaney,Andrew Updegrove,Kara H. Woo,Kara H. Woo,Tal Yarkoni +16 more
Journal ArticleDOI
Structural biology meets data science: does anything change?
TL;DR: It is posited that the answer to the above question is yes: can these two fields impact one another in deep and hitherto unforeseen ways?
Journal ArticleDOI
Statistically rigorous automated protein annotation
Werner G. Krebs,Philip E. Bourne +1 more
TL;DR: A combined statistical method that enables robust, automated protein annotation by reliably expanding existing annotation sets is described, based on relevant experimental information, and can also provide human reviewers with a reliability score for both new and previously classified proteins.