Professor, Nuffield Departments of Population Health & Medicine, University of Oxford
Adjunct Professor, Department of Medicine, UC San Diego
Member, Moores Cancer Center, UC San Diego
Director, ARPA-H ADAPT, Dynamic Digital Tumors for Precision Oncology Project
Director, NIH Bridge2AI, Cell Maps for AI (CM4AI) Data Generation Project
Co-Director, NIH NCI, Cancer Cell Map Initiative (CCMI)
Email: tideker@ucsd.edu
Assistant: idekeradmin@ucsd.edu
Ideker is the Director of the Big Data Institute at University of Oxford, with joint faculty appointments in the Nuffield Department of Population Health and the Nuffield Department of Medicine. He is also adjunct Professor of Medicine at UC San Diego where he has been on the faculty since 2003. He serves as Director or Co-Director of several international research initiatives and centers, including the Cancer Cell Map Initiative, the Bridge2AI Cell Maps for Artificial Intelligence Project, and the ARPA-H Digital Tumors Precision Oncology Center. His 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, he produced numerous maps of protein-protein, transcriptional, and genetic networks in model organisms and humans, along with widely used Cytoscape network analysis software. His studies created methodologies that are now core concepts in bioinformatics, including generation of transcriptional networks to explain genome-wide expression patterns, network alignment and evolutionary comparison, and network biomarkers, which enable multigenic definitions of patient subtypes and treatment responses. His lab also introduced experimental network mapping techniques, including synthetic-lethal interaction mapping with CRISPR/Cas9 and characterization of differential interactions across conditions and time. These technologies have broadly informed the mechanisms by which diverse genetic alterations drive cancer, neurological disorders, and drug resistance. Recently he demonstrated an end-to-end pipeline for mapping the structure of human cells over a broad scale range, based on fusion of protein networks with immunofluorescence imaging. He has also recently shown that network maps provide a substrate for deep learning models of cell structure and function, with basic implications for the construction of intelligent systems in precision oncology. Finally, he and collaborators showed that large parts of the methylome are remodeled with age, leading to the first epigenetic clock and the rapidly expanding field of epigenetic aging. Finally, Ideker has mentored numerous postdoctoral scholars and graduate students, with many former trainees who have successfully progressed to independent faculty positions.