Research Projects
The Ideker Laboratory seeks to create artificially intelligent models of cancer and other diseases for the translation of patient data to precision diagnosis and treatment. In doing so, we hope to address fundamental questions in systems biology and bioinformatics, including: What are the genetic and molecular networks that promote cancer? How can we best chart these? How do we use knowledge of these networks in intelligent systems for translation of genotype to phenotype?
Click an icon to learn more about our current research areas:
Meet the Ideker lab
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.
Join Our Team
The Ideker Laboratory is in continual open recruitment for excellent postdoctoral scholars, graduate students, and software engineers.
Recent News & Publications
Spotlight on CCMI publications in Science (2021 Oct)
Fan Zheng* & Mark Kelly*, et al. Interpretation of cancer mutations using a multiscale map of protein systems. Science. 2021 Oct 1. *Equal Contribution [PDF] [PubMed]
Kim M, et al. A protein interaction landscape of breast cancer. Science. 2021 Oct 1. [PDF] [PubMed]
Swaney DL, et al. A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity. Science. 2021 Oct 1. [PDF] [PubMed]
Recent Press:
- “Studies Delve Deep into the Protein Machinery of Cancer Cells.” NCI (4 Nov 2021)
- “From COVID to cancer, gene-mapping tool could ‘revolutionize’ treatment“. SF Chronicle (2 Oct 2021)
- “Moonshot Project Aims to Understand and Beat Cancer Using Protein Maps“. Singularity Hub (5 Oct 2021)
- “Looking Beyond DNA to See Cancer with New Clarity,” features Trey Ideker, PhD.
- See also FierceBiotech, AXIOS, MSN, and Times of San Diego
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.
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.
Erica Silva, et al. Genome-Wide Dynamic Evaluation of the UV-Induced DNA Damage Response. G3 (2020 Sept). [PDF] [PubMed]
Research Centers & Affiliates
