W. G. Pritchard Lab Seminar: 4:00-5:00 PM, 101 Osmond Laboratory

	            **Tuesday October 28, 2003**
	
An integrated approach for protein function prediction

Fengzhu Sun

Molecular and Computational Biology Program
Department of Biological Sciences
University of Southern California

Abstract:

Assigning functions to novel proteins is one of the most important problems 
in the post-genomic era. Many different sources of genomic data, such as
protein-protein physical interactions, genetic interactions, gene 
expressions, and domain structure contain information about protein 
function.  We developed a novel approach that employs the theory of Markov 
random fields to infer a protein's functions using an integrated approach 
combining various sources of biological data. The model is flexible in that 
other protein pairwise relationship information and features of individual 
proteins can be easily incorporated. We apply our integrated approach to 
predict functions of yeast proteins.