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[主讲人: 钱玉麟] [时间: 2010-10-18 10:50:00]
钱玉麟教授简介：
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Professor Chin received the B.A.Sc. degree from the University of Toronto, Canada, in 1972, and the M.S., M.A. and Ph.D. degrees from Princeton University, in 1974, 1975, and 1976, respectively. Since 1975,he has taught at the University of Maryland, Baltimore County,University of California, San Diego, University of Alberta, Chinese University of Hong Kong, and University of Texas at Dallas. He joinedthe University of Hong Kong (HKU) in 1985, where he is the Chair of the Department of Computer Science and was the founding Head of the department from its establishment until December 31, 1999. Between 1992-1996, he served as the Associated Dean of Graduate School. In 1996,Prof. Chin was elected to the grade of IEEE Fellow.Professor Chin is currently serving as Manager Editor of the International Journal of Foundations of Computer Science and is also on the editorial boards of several journals. He has served on the program committees and as conference chairman of numerous international workshops and conferences. Professor Chin's research interests include design and analysis of algorithms, on-line algorithms, and bioinformatics。
.Title：Conserved Patterns in Bioinformatics
Time：2010年10月18日上午10：50~11：50
Place：创新园大厦A331
Abstract: Study of conserved patterns is fundamental in computational biology, for example, regulatory motifs (conserved patterns) in DNA sequence and conserved biological interactions in the comparative analysis of different species. These studies, if done by the traditional way using purely biological experiments, would be expensive, laborious and time-consuming if not impossible. With the advancement of microbiology technology in experiments, large volume of data on genome sequences and biological interactions have become available from experiments on which computational analysis can be done.
In this talk, we shall present problems and algorithms on conserved patterns in the study of DNA sequences, in particular when the regulatory motifs are represented by strings or probability matrices.
Conserved (similar) biological processes in different species, for example, interaction networks including protein interaction networks, metabolic networks, gene regulatory network and signal transduction networks, have attracted much attention recently. In this talk, we shall also discuss problems and approaches in analyzing and discovering conserved patterns in these networks.
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