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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.