Dr. Trey Ideker

​​​​​​Dr. Trey Ideker
Dr. Ideker is a Professor of Medicine at UC San Diego. He is the Director of the National Resource for Network Biology, the San Diego Center for Systems Biology,  and the Cancer Cell Map Initiative. He is a pioneer in using genome-scale measurements to construct network models of cellular processes and disease.

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About the Ideker Lab

The long-term objective of the Ideker Laboratory is to create artificially intelligent models of cancer and other diseases for translation of patient data to precision diagnosis and treatment. We seek to advance this goal by addressing fundamental questions in systems biology and bioinformatics, including: What are the genetic and molecular networks that promote cancer, and how can we best chart these? How do we use knowledge of these networks in intelligent systems for translation of genotype to phenotype?

The Ideker Lab is a member of the Cancer Cell Map Initiative (CCMI), the Psychiatric Cell Map Initiative (PCMI), the Host-Pathogen Map Initiative (HPMI)the San Diego Center for Systems Biology (SDCSB), the National Resource for Network Biology (NRNB), and the Institute for Genomic Medicine (IGM).

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Available Positions 


National Resource for Network Biology San Diego Center for Systems Biology 

Featured News

Lytle NK, et al. A Multiscale Map of the Stem Cell State in Pancreatic Adenocarcinoma. Cell. 2019 Mar 29.  [PDF] [PubMed]

Yu MK, Ma J, et al. DDOT: A Swiss Army Knife for Investigating Data-Driven Biological Ontologies. Cell Syst. 2019 Mar 27. [PDF] [PubMed]

Wallace ZS, et al. On entropy and information in gene interaction networks. Bioinformatics. 2019 Mar 1. [PDF] [PubMed]

Ribosomal DNA Can Predict an Animal’s Age. Abby Olena, The Scientist Magazine. (Feb 14, 2019). PDF

Trey Ideker included in new listing of highly cited researchers in the top 1% for their field. 45 UC San Diego Faculty Named Most Influential in Their Fields. Michelle Franklin, UC San Diego News Center. (November 28, 2018) 

JMB Special Issue: Theory and Application of Network Biology Toward Precision Medicine. (14Sept 2018) Edited by Barry Demchak, Jason F. Kreisberg, Juan I. Fuxman Bass. Cover art by Kivilcim Ozturk, Michelle Dow and Hannah Carter. 

Genetic Mutations of Appendix Cancer Identified, May Impact Treatment,” features Drs. John Paul Shen, Trey Ideker, and Olivier Harismendy

Visible Machine Learning for Biomedicine. Michael Yu, et al. CELL. 14 JUN 2018. [PDF] 

"Gems in the 'Junk' - Noncoding mutations found to be a major mechanism in cancer," DDN News. (22 May 2018). 

"Cracking Open the Black Box of AI with Cell Biology." IEEE Spectrum, (13 Mar 2018).

"Researchers Identify Hundreds of Mutations outside of Coding Genes that Influence Tumor Gene Expression," SCI NEWS. (06 Apr 2018)

"CRISPR-based mapping of genetic interactions"  Nature Reviews | Genetics (2017)

"Gene editing used to find cancer's genetic weak spots." Features video interview with Dr. John Paul Shen. SD Union Tribune, (2017) [Printed Article