Philip E. Bourne, Ph.D.

1971-1980 Chemistry Flinders University, Australia, Bedford Park, South Australia, Australia 
 1979-1981 Biochemistry University of Sheffield, Sheffield, England, United Kingdom 
 1981-1995 Biochemistry and Molecular Physics Columbia University, New York, NY 
 1995-2014 San Diego Supercomputer Center/Pharmacology University of California, San Diego, La Jolla, CA 
 2014- Office of the Director NIH (NCI) 
 2017- School of Data Science, Biomedical Engineering University of Virginia, Charlottesville, VA 
"Philip Bourne"

Philip Eric Bourne (born 1953) is a United States researcher in health informatics. He is the first Associate Director for Data Science at the National Institutes of Health, where his projects include managing the Big Data to Knowledge initiative. Bourne was trained as a physical chemist in the mid to late 1970s and obtained his PhD in 1979 at the The Flinders University of South Australia. He moved to the University of Sheffield to do postdoctoral research during 1979-1981, followed by a move to Columbia University, New York, in 1981. In 1995 he moved to University of California, San Diego, where he was a Professor in the Department of Pharmacology. In 2014, he moved to NIH to become its Associate Director for Data Science. (Source: Wikipedia)


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Peter Mossel research assistant 1985-1990 Columbia
Janie Weiss research assistant 1987-1994 Columbia
Susan Kisler research assistant 1991-1994 Columbia
Eric D. Scheeff grad student 2003 UCSD
Jenny Gu grad student 2006 UCSD
Song Yang grad student 2007 UCSD
Kristine M. Briedis grad student 2008 UCSD
Roger Larken Chang grad student 2012 UCSD
Eli Draizen grad student 2018-2022 UVA (Chemistry Tree)
Werner G. Krebs post-doc 2002-2004 UCSD
Ilya Shindyalov post-doc 1992-2005 UCSD
Eric David Scheeff post-doc 2003-2006 UCSD (Chemistry Tree)
Stella Veretnik post-doc 2002-2010 UCSD
Cameron Mura research scientist 2018- UVA (Chemistry Tree)
Lei Xie research scientist 2004-2011 UCSD
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Mura C, Bourne PE. (2023) Ten simple rules for serving as an editor. Plos Computational Biology. 19: e1010911
Cai T, Xie L, Zhang S, et al. (2023) End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins. Plos Computational Biology. 19: e1010851
Bourne PE, Draizen EJ, Mura C. (2022) The curse of the protein ribbon diagram. Plos Biology. 20: e3001901
Gallo K, Goede A, Mura C, et al. (2022) A Comparative Analysis of COVID-19 Vaccines Based on over 580,000 Cases from the Vaccination Adverse Event Reporting System. Vaccines. 10
Gohlke BO, Zincke F, Eckert A, et al. (2022) Real-world evidence for preventive effects of statins on cancer incidence: A trans-Atlantic analysis. Clinical and Translational Medicine. 12: e726
Zhao Z, Xie L, Bourne PE. (2021) Correction to "Structural Insights into Characterizing Binding Sites in Epidermal Growth Factor Receptor Kinase Mutants". Journal of Chemical Information and Modeling
Cai T, Xie L, Chen M, et al. (2021) Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology. Research Square
Mura C, Preissner S, Preissner R, et al. (2021) A Birds-Eye (Re)View of Acid-Suppression Drugs, COVID-19, and the Highly Variable Literature. Frontiers in Pharmacology. 12: 700703
Mura C, Preissner S, Nahles S, et al. (2021) Real-world evidence for improved outcomes with histamine antagonists and aspirin in 22,560 COVID-19 patients. Signal Transduction and Targeted Therapy. 6: 267
Donlan AN, Sutherland TE, Marie C, et al. (2021) IL-13 is a driver of COVID-19 severity. Jci Insight
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