Computer Science and Engineering
Chief of Medical Genetics ,
Bioinformatics and systems biology; computational modeling of cellular regulatory networks; yeast genetics
Mapping genetic networks in human disease
The past decade has seen an explosion in “genome-era” technologies which profile genes, proteins, metabolites and the intricate web of interconnections among them. These advances are revealing complex genetic networks that underlie human biology and patient health. Mapping genetic networks will be essential information as doctors struggle to interpret the flood of genetic and clinical data that can now be collected for a patient. The Ideker lab is working in several areas which we believe will be critical for enabling tomorrow's clinicians to use genetic networks to diagnose and treat disease.
Mapping the genetic network underlying the response to DNA damage. Failure of cells to respond to DNA damage is a primary step in the onset of cancer and is a key mechanism of environmental toxicity. Consequently, cells have evolved complex repair and stress responses that are highly conserved across the eukaryotic kingdom, from yeast to humans. We are using genome-scale technologies such as ChIP-sequencing and synthetic-lethal screens to map how the cell's transcriptional network is remodeled by DNA-damaging conditions. For an example of our network mapping efforts for DNA damage pathways, see Workman et al. Science. 312 (5776):1054-1059 (2006).
Network-based biomarkers for disease diagnosis and personalized medicine. Genetic “biomarkers” are typically thought of as individual genes and proteins—for example using prostate specific antigen (PSA) as a marker for prostate cancer. Recently, we have shown that genetic networks can also serve as powerful biomarkers, and in many cases are more predictive than any individual gene [Chuang et al. Mol Syst Biol. 3:140 (2007)]. Our approach is to use high-throughput DNA sequencing to profile all of the genes expressed in the tissue of a particular patient, and to then project these genes onto the known human genetic network map to identify pathways that are predictive of disease. This “network-based” biomarker approach has shown success in diagnosis of metastatic breast cancer, and we are now working with Dr. Thomas Kipps at the UCSD Moores Cancer Center to diagnose Chronic Lymphocytic Leukemia. We are also collaborating with Drs. Kang Zhang and Joe Gleason to identify the common pathways by which genetic defects affect macular degeneration and neuronal development, respectively.
Network analysis between pathogen and host. Genetic network mapping also has application to infectious disease, for example by targeting drugs to networks that are present in a pathogenic organism but absent from its human host. In collaboration with Dr. Stanley Fields at University of Washington and Prolexys Pharmaceuticals, we have used network comparisons to study the protein interaction network of Plasmodium, the pathogenic protozoan that causes malaria— see Suthram et al. Nature 438(7064):108-12 (2005). Surprisingly, the Plasmodium protein network was quite divergent from other known networks. We are also working with Dr. Sumit Chanda at the Burnham Institute to identify protein networks essential for HIV infection, and how those that differ from RNA and DNA viruses—see Konig et al., Cell 135(1):49-60 (2008).
For professional distribution of our network-based technologies, we are developers of the Cytoscape platform, an Open-Source software environment for visualization and analysis of biological networks and models (http://www.cytoscape.org/).
Division of Medical Genetics website (medgenetics.ucsd.edu).
Trey Ideker, Ph.D. is Division Chief of Medical Genetics at the UC San Diego School of Medicine. He also serves as Professor of Medicine and Bioengineering, Adjunct Professor of Computer Science and Member of the Moores UCSD Cancer Center. Ideker received Bachelor’s and Master’s degrees from MIT in Electrical Engineering and Computer Science and his Ph.D. from the University of Washington in Molecular Biology under the supervision of Dr. Leroy Hood. He is a pioneer in using genome-scale measurements to construct network models of cellular processes and disease. His recent research activities include assembly of networks governing the response to DNA damage, development of software for protein network cross-species comparisons, and network-based diagnosis of disease. Ideker serves on the Editorial Boards for Bioinformatics and PLoS Computational Biology, Board of Directors for US-HUPO and the Cytoscape Consortium, and is a regular consultant for companies such as Monsanto, Genstruct, and Mendel Biotechnology. He was named one of the Top 10 Innovators of 2006 by Technology Review magazine and was the recipient of the 2009 Overton Prize from the International Society for Computational Biology. His work has been featured in news outlets such as The Scientist, the San Diego Union Tribune, and Forbes magazine.
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