Phylogenetic Estimation for Complex Evolutionary Processes

Li-San Wang, University of Pennsylvania

Tuesday, February 28
10:15am - SENSQ 5317

Meet the speaker at 10:00am

Hosted by Kirk Pruhs

Abstract

Stochastic models of sequence evolution, since their introduction in the 60s, have inspired the development of numerous computational and statistical methods for phylogeny reconstruction; these methods have been widely successful in reconstructing the evolutionary history of genes and species. Standard stochastic models have three essential features: (1) the domain of mutation is a concatenation of multiple independently distributed sites, each following a simple, identical stochastic process; (2) the species share a common evolutionary history; and (3) the evolutionary history is a branching process (tree).

This talk is an overview of my research on complex evolutionary processes -- processes that lack at least one of the three features of these standard models. In these cases, new stochastical models need to be developed. Moreover, the new problems have higher computational complexity and requires novel strategies.

I will cover three such processes: the process of gene order evolution (complex domain of mutation), the process of horizontal gene transfer (non-tree evolutionary history), and the progression of gene expression profiles in cancer (species do not share a common history). For each process, I will formulate the estimation problems, identify computational and statistical issues, and present our current results and future research directions.

Biography of Speaker

Li-San Wang received his B.S. (1994) and M.S. (1996) in Electrical Engineering from the National Taiwan University. He then received his M.S. (2000) and Ph.D. (2003) from the University of Texas at Austin, both in Computer Sciences. Currently he is a postdoctoral fellow at the Department of Biology, University of Pennsylvania. His research interests include computational phylogenetics, comparative genomics, and microarray analysis.