Abstract: Cancer is an evolutionary process driven by somatic mutations that accumulate in a population of cells that form a tumor. In the past few years, high-throughput DNA sequencing technologies have enabled the measurement of these mutations across thousands of individual tumors. Despite this wealth of data, our understanding of the cancer mutational landscape remains incomplete. In this talk, I will describe algorithms to identify networks of interacting mutations across cancer patients and to infer the evolution of mutations within a tumor from a single patient. Together these approaches help address key analytical challenges in translating measurements of somatic mutations into deeper insights about the processes that drive cancer development.
Bio: Ben Raphael is a Professor of Computer Science at Princeton University. He received his Ph.D. in Mathematics from University of California, San Diego, and then began research in computational biology and bioinformatics as a postdoctoral fellow. From 2006-2016, he was an Assistant and Associate Professor of Computer Science at Brown University, and from 2013-2016 was also the Director of the Center for Computational Molecular Biology (CCMB). He is the recipient of the Alfred P. Sloan Research Fellowship, the NSF CAREER award, and a Career Award at the Scientific Interface from the Burroughs Wellcome Fund.