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

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Meet the Team

The Ideker Laboratory has welcomed many distinguished researchers over the years — ranging from undergraduates to visiting scientists. Click buttons below to view Dr. Ideker’s profile and meet our past and present lab members. 

Open Projects and Positions

The Ideker Laboratory is in continual open recruitment for excellent postdoctoral scholars, graduate students, and software engineers. 


New Publication Alert

Rare and common variants associated with alcohol consumption identify a conserved molecular network

Our latest study explores the genetic basis of alcohol consumption by examining both common and rare genetic variants, uncovering a shared molecular network involved in alcohol metabolism and neuropsychiatric traits. This integrated approach provides a comprehensive understanding of the genetic factors influencing alcohol use, highlighting potential targets for future research and intervention.

Read the full study here.

      Recent Publication

      In vitro evolution and whole genome analysis to study chemotherapy drug resistance in haploid human cells

      We released an exciting new publication on the  use of haploid human cells to study drug resistance mechanisms. This research helps us understand how cancer fights back against treatment and could lead to better therapies.

      Check out the publication here.

          Cell Maps for Artificial Intelligence

          AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines

          Read our recent publication. This article describes the Cell Maps for Artificial Intelligence (CM4AI) project and its goals, methods, standards, current datasets, software tools, status, and future directions. CM4AI is the Functional Genomics Data Generation Project in the U.S. National Institute of Health’s (NIH) Bridge2AI program. Its overarching mission is to produce ethical, AI-ready datasets of cell architecture, inferred from multimodal data collected for human cell lines, to enable transformative biomedical AI research.


              Drugst.One — a plug-and-play solution for online systems medicine and network-based drug repurposing

              Drugst.One transforms specialized computational medicine tools into user-friendly, web-based utilities for drug repurposing, enabling intuitive modeling and analysis of protein-drug-disease networks with just three lines of code. Successfully integrated with 21 systems medicine tools, Drugst.One streamlines drug discovery, allowing researchers to focus on essential pharmaceutical treatment research

              Visit for more information.

                  Proceedings of the National Academy of Sciences

                  Epigenetic age can fluctuate by five years in a single day

                  “It’s a study I’ve been waiting to see for a long time.” – Trey Ideker

                  Epigenetic changes—in particular, DNA methylation, which can regulate gene expression—are thought to accumulate over years or decades, “but not over short periods,” says Art Petronis, a chrono-epigeneticist with dual appointments at the University of Toronto, Canada, and Vilnius University in Lithuania. But in a recent study in Aging Cell, Petronis and coauthors found that epigenetic age actually fluctuates throughout the course of a day.

                  PNAS: Coenzyme Q10 trapping in mitochondrial complex I underlies Leber's hereditary optic neuropathy - Doheny Eye InstituteAmy McDermott
                  May 3, 2024

                      Study co-author Katherine Licon, photographed here at the bench, is lab manager for the Ideker Lab at UC San Diego. Photo by Erik Jepsen/UC San Diego.
                      Simulated Chemistry: New AI Platform Designs Tomorrow’s Cancer Drugs

                      The new platform helped UC San Diego scientists synthesize 32 potential multi-target cancer drug

                      Explore the advancements at UC San Diego with our recent publication, where our innovative AI platform is revolutionizing cancer drug development. Dive deeper into how this technology is setting new standards in drug design and pharmaceutical sciences. 

                      Related Press:

                          UCSD School of Medicine uses AI to predict which drugs to use to treat cancer patients

                          Discover our recent publication highlighted by four simultaneous news coverage articles. Delve into an informative interview with Dr. Ideker and Abbie Black from CBS News

                          Related Press: 

                              Spotlight on Cancer Cell Map Initiative
                              A New Map
                              Smartly Done
                              Forbes 30 Under 30 Class of 2023

                              Congratulations to Dr. Yue Qin, Ideker Lab Graduate, for getting two major awards! Yue was selected to join the Forbes 30 Under 30, Class of 2023 (read more here and here) and also awarded the 2023 UCSD Chancellor’s Dissertation Medal for the Jacobs School of Engineering.

                              Dr. Ideker is a Clarivate Highly Cited Researcher for 4 straight years , from 2020 to 2023. This highly anticipated annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade.  View the complete 2021 Highly Cited Researchers list.

                              Research Centers & Affiliates