COLLOQUIUM
Department of Computer Science and Engineering
University of South Carolina
 
Study of microRNAs: a Biology Problem with Computational Challenges

Xuefeng Zhou

Department of and Computer Science and Engineering
Washington University

Date: April 10, 2008
Time: 1530-1700
Place: Swearingen 3C02

Abstract

Repression of gene expression is an important regulatory mechanism
that controls many biological processes such as development, cell
proliferation and differentiation.  The discovery of microRNAs
(miRNAs) has broadened our perspectives on the mechanisms of
down-regulation of gene expression and shed light on an entirely novel
level of post-transcriptional regulation. Besides their important
functions in the development of animals and plants, miRNAs have been
shown to play crucial roles in the pathogenesis of many diseases, such
as cancer.  Since the discovery of the very first miRNA, almost all
progress on the study of miRNA has resorted to help from computational
approaches. In this talk, I will first present our recent work on the
prediction of novel miRNAs. Available computational methods require
many known miRNAs, clear genome annotations, and evolutionary
conservation information. I will present a novel ranking algorithm
based on random walks to identify novel miRNAs computationally. In
contrast to existing algorithms, our algorithm uses very few positive
samples, requires no negative samples, and does not rely on genome
annotations. Secondly, I will present our work on genome-wide
characterization of promoters of miRNA genes. This is the first piece
of work in this field and has been well accepted by
biologists. Thirdly, I will discuss module discovery in miRNA
regulatory networks. Modularity is one of the most prominent
properties of real-world complex networks including biological
networks. Here, I will address the issue of module identification in
bipartite networks and report on a novel algorithm especially suited
for module detection in them. I will show how to analyze the modules
in the miRNA regulatory networks by formulating them into bipartite
networks. Finally, I will conclude with an overview of my research
interests and my plan for future research.

Xuefeng Zhou is a fifth-year graduate student in the Department of
Computer Science and Engineering at Washington University in Saint
Louis. His advisor is Dr. Weixiong Zhang. He received his MS degree in
computer science from Illinois Institute of Technology in 2003. Before
that, he obtained his MS degree in biochemistry and molecular biology
from Peking Union Medical College, and BS degree in biology from
Peking (Beijing) University. He expects to receive his Ph.D degree in
computer science in June, 2008.  His primary research interests lie in
bioinformatics/computational biology and data mining, and his current
research focuses on computational studies of different aspects of
miRNAs as well as other small RNAs.