Trey Ideker

Trey Ideker is Director of the Big Data Institute. Previously, he served as a faculty member at UC San Diego since 2003, with current appointments in the Departments of Medicine, Bioengineering, and Computer Science and Engineering. Additionally, he holds leadership positions as Director or Co-Director of several federally-funded research centres, including the Cancer Cell Map Initiative, the Bridge2AI Functional Genomics Data Generation Program, and, most recently, an ARPA-H ADAPT Precision Oncology Centre. He is also a Visiting Member at the Ellison Medical Institute (EMI),

Ideker received BS and MEng degrees in Computer Science from MIT and a PhD in Genome Sciences from the University of Washington under Drs. Lee Hood and Dick Karp. He was then a David Baltimore Fellow at the Whitehead Institute before joining the UCSD faculty in 2003. He was named a Top 10 Innovator by Technology Review, received the 2009 ICSB Overton Prize, and is a Fellow of the AAAS, AIMBE and ISCB organisations. Ideker previously served as a member of the Board of Scientific Advisors to the NIH National Cancer Institute and National Human Genome Research Institute. He also serves on the editorial boards of Cell, Cell Systems, PLoS Computational Biology, and Molecular Systems Biology. Since 2020 he has been named a Web of Science Highly Cited Researcher (top 1% by citations). Ideker has published >280 scientific articles to date, which have been cited a total of >119,000 times with a current h-index of 111.

The Ideker laboratory has led seminal studies establishing the theory and practice of systems biology, including systematic techniques for elucidating human cell architecture and its molecular networks. From 2001–present, his laboratory has produced numerous maps of protein-protein, transcriptional, and genetic networks in model organisms and humans (in collaboration with trainees and co-investigators), along with widely used Cytoscape network analysis software (with Gary Bader and others). His studies created methodologies that are now core concepts in bioinformatics, including generation of transcriptional networks to explain genome-wide expression patterns (with Leroy Hood), network alignment and evolutionary comparison (with Richard Karp and Roded Sharan), and network biomarkers, which enable multigenic definitions of patient subtypes and treatment responses.