From Network Connectivity to Cancer

Guest Speaker: Ron Shamir, Tel Aviv University Professor Date: March 17th, 2009 Time: 2:30pm Location: Room 1202, CSE Building, UC San Diego Host: Pavel Pevzner and Vineet Bafna [event website]

DESCRIPTION/ABSTRACT: This seminar is organized by the Center for Algorithmic and Systems Biology (CASB) at Calit2 UCSD. Abstract: High throughput experimental techniques are generating larger and larger biomedical datasets, with great potential to further our understanding of basic life and disease processes. However, integrated analysis methods of these data that will provide focused biomedical insights is still a major challenge, especially when the data are heterogeneous.  This talk will describe some of our methods for joint analysis of gene expression data, protein interaction networks, and clinical data from patient records. A common thread in our approach is the combination of graph algorithms with probabilistic modeling. Interestingly, invoking graph connectivity seems useful in many cases. I will demonstrate the methods on specific applications related to cancer and stem cells. Joint work, in parts, with Igor Ulitsky (Tel Aviv University), Richard M. Karp (UC Berkeley) Louise Laurent and Jeanne Loring (Scripps). SPEAKER BIO: Ron Shamir is a professor at the Blavatnik School of Computer Science, Tel Aviv University (TAU). He received a B. Sc. In Mathematics and Physics from the Hebrew University in 1977, and a PhD in Operations Research from UC Berkeley in 1984. He is on the faculty of TAU since 1987. He holds the Raymond and Beverly Sackler chair of Bioinformatics, and heads the Edmond J. Safra Bioinformatics Program at TAU.  He develops novel algorithms to advance biology. His interests include gene expression analysis, comparative genomics, gene regulation, systems biology and disease bioinformatics. He is on the editorial board of eleven scientific journals and series, was a member of the RECOMB Steering Committee for 13 years since its foundation, and has published over 190 scientific papers.