Title: "Sample Motifs on Phylogenetic Trees"
Speaker: Dr. Xiaoman (Shawn) Li, Department of Statistics, Harvard University
Place: Smith Hall (SMTH) 108; Tuesday, 4:30pm


I will present a Gibbs sampler to find motifs by simultaneously using the overrepresentation property and evolutionary conservation property of motifs. The method has been applied to search regulatory motifs in four yeast species based on ChIP-chip data in S. cerevisiae and obtained 20% higher accuracy than two current popular methods. We also discovered cis-regulatory elements that govern the tight regulation of ribosomal protein genes in 2 distantly related insects by using this method. These results demonstrated that, the sampler can find motifs not only in small gene sets but also in gene sets containing weak motifs. Unlike most alignment-based motif finding methods, this method is applicable also to divergent species where alignment is unreliable.

This is a Statistics Bioinformatics COALESCE candidate interview

Click here for a full scheule of BIOINFORMATICS SEMINARS, past and present.