Integrated analysis of cancer data: multi-omic clustering and personalized ranking of driver genes

updated: 26.02.2019

Seminar

Thursday February 14 2019, at 16:00

UC Berkeley, 125 Li Ka Shing Center

 

Seminar Title:

Integrated analysis of cancer data: multi-omic clustering and personalized ranking of driver genes

 

Speaker:

Prof. Ron Shamir, School of Computer Science, Tel Aviv University

 

Abstract:

Large biological datasets are currently available, and their analysis has applications to basic science and medicine. While inquiry of each dataset separately often provides insights, integrative analysis may reveal more holistic, systems-level findings. We demonstrate the power of integrated analysis in cancer on two levels: (1) in analysis of one omic in many cancer types together, and (2) in analysis of multiple omics for the same cancer. In both levels we develop novel methods and observe a clear advantage to integration. We also describe a novel method for identifying and ranking driver genes in an individual's tumor and demonstrate its advantage over prior art.

 

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