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.
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Combating Chagas Disease Through Inhibition of Tiam1, a Rho GTPase Guanine Nucleotide Exchange Factor
TL;DR: An in silicodrug repurposing strategy to correlate drug-protein interactions with positive clinical outcomes and results from both computational and in vitrostudies indicate possible inhibition of phosphoinositides via Posaconazole, preventing Rho GTPase-induced proliferation of T. cruzi, the etiological agent of Chagas Disease.
Journal ArticleDOI
Changes to NIH grant system may backfire
Peter D. Karp,Gavin Sherlock,John A. Gerlt,Ida Sim,Ian T. Paulsen,Patricia C. Babbitt,Keith R. Laderoute,Lawrence Hunter,Paul W. Sternberg,John Wooley,Philip E. Bourne +10 more
TL;DR: Although the authors appreciate the many challenges facing the current NIH grant system and applaud attempts at reform, they believe that several of the changes planned will cause more harm than good.
Journal ArticleDOI
Correction: Ten Simple Rules for Selecting a Postdoctoral Position
Philip E. Bourne,Iddo Friedberg +1 more
TL;DR: A correction note is found in the section called Rule 1: Select a Position That Excites You, where the sentence, ‘‘Just because the mentor is excited about the project does not mean that you will be six months into it’’, had the two words '‘that'’ and '’you' switched.
Proceedings ArticleDOI
Statistical and visual morph movie analysis of crystallographic mutant selection bias in protein mutation resource data
Werner G. Krebs,Philip E. Bourne +1 more
TL;DR: A comprehensive statistical analysis of PMR mutants and makes available morph movies from PMR structure pairs, allowing visual analysis of conformational change and the ability to distinguish visually between conformational changes due to motions and mutations.
Posted ContentDOI
Ten simple rules for considering preprints
TL;DR: These rules, if they pass review, will appear as part of the PLOS Computational Biology Ten Simple Rules Collection, and cover such issues as reward, incentives, speed of dissemination, quality, scooping, and record of priority.