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.
News
Webinar: Building a Mind for Cancer with Trey Ideker, PhD
AI simulates how cancer cells respond to therapy, guiding optimal treatment strategies.
Despite the growing interest in using AI to forecast cancer drug responses, the complexity of tumor biology poses significant challenges. This webinar with Trey Ideker will delve into AI models that predict drug reactions in cancer, highlighting crucial molecular pathways for better drug development.
Topics to be covered
- Constructing an interpretable deep learning model for predicting drug responses
- Developing neural network predictive models for various tissue types and clinical settings
Join us on Tuesday, March 26th, 2024 | 1:00 PM – 2:00 PM Eastern Time
This webinar will be available to view live and on demand.
Spotlight: UC San Diego 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:
- AI Harnesses Tumor Genetics to Predict Treatment Response. Miles Martin, UC San Diego Today. (2024 Jan 18) [PDF]
- Scientists use AI to predict when cancer cells will resist chemotherapy. Sejal Sharma, Interesting Engineering. (2024 Jan 18) [PDF]
- AI Uses Tumor Genetics for Prediction of Treatment Response. Mary Ann Liebert, Inside Precision Medicine. (2024 Jan 18) [PDF]
- AI points to better and new cancer treatments. Susan Robertson, Innovators Magazine. (2024 Jan 18) [PDF]
- “Hundreds of proteins work together in complex arrangements to replicate DNA. Mutations in any one part of this system can change how the entire tumor responds to chemotherapy.”
- UCSD School of Medicine researchers use AI models to predict chemotherapy treatment responses. Eru Ishikawa, The UCSD Guardian. (2024 Jan 29) [PDF]
- Machine Learning Models Help Predict Medication Responses. Barbara Vann, National Cancer Institute (NIH). (2024 Feb 5) [PDF]
Spotlight on Cancer Cell Map Initiative
A New Map
Smartly Done
Forbes 30 Under 30 Class of 2023
Yue Qin, et al. A multi-scale map of cell structure fusing protein images and interactions. Nature. 2021. [PubMed] [PDF]
Recent press: “Studies Delve Deep into the Protein Machinery of Cancer Cells.” NCI (4 Nov 2021)
A New Map Reveals the Complicated World in Which Cells Seek to Repair Damaged DNA.
Scott LaFee, UC San Diego Today. (2023 May 22) [PDF]
Nicole Mlynaryk, UC San Diego Today. (2023 May 18)
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.
Yue Qin, et al. A multi-scale map of cell structure fusing protein images and interactions. Nature. 2021. [PubMed] [PDF]
Recent press: We Might Not Know Half of What’s in Our Cells, New AI Technique Reveals.
Tina Wang, et al. Quantitative Translation of Dog-to-Human Aging by Conserved Remodeling of the DNA Methylome. Cell Systems (2020 Aug). [PDF] [PubMed]
Recent Press: Old Dogs, New Research and the Secrets of Aging. New York Times (2020)
Brent M. Kuenzi, Jisoo Park, et al. Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells. Cancer Cell (2020 Oct). [PDF] [PubMed]
Recent Press: DrugCell: New Experimental AI Platform Matches Tumor to Best Drug Combo.
Dr. Ideker is a Clarivate Highly Cited Researcher two years in a row, in both 2020 and 2021. 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.
Dr. Ideker is a Clarivate Highly Cited Researcher two years in a row, in both 2020 and 2021. 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
