报告人：Yufeng Wu，University of Connecticut, USA.
报告时间：2013年6月8日下午14：00
报告地点：科技大厦２０２
报告内容简介：
群体遗传学一个介于遗传学，分子生物学，数学，统计和计算之间的交叉学科。目前随机过程，概率与统计分析在群体遗传学被广泛应用。随着基因组数据量的不断扩大，计算正成为群体遗传学的一个重要工具。在这个讲座里，将会先对群体遗传学中的一个重要理论：溯祖理论做一个简短的概述。然后，会介绍我的一个近期的基于溯祖理论的群体进化的工作。讲座的重点将放在基于溯祖理论的高效计算。
Population genetics is an interdisciplinary branch of genetics, which involves genetics, mathematics, molecular biology, statistics and computation. While tools such as stochastic process, probability and statistical analysis are widely used in population genetics study, computation now plays an increasingly important role with the ever-increasing data size. In this talk, I will first give a short tutorial about an important theory in population genetics: coalescent theory. Then I will present my recent work on the application of coalescent theory in the understanding of population evolution. The focus is on the efficient computation based on the coalescent theory.
报告人简介：
Yufeng W u教授是美国康涅狄格大学计算机科学与工程系的助理教授。 19９ 4年在清华大学获得学士学位， 1998年在美国伊利诺伊大学香槟分校获得计算机硕士学位 ,2007年在美国加州大学戴维斯分校获得计算机科学博士学位。他在生物信息学的算法研究工作多年，尤其是专注于群体遗传学、进化 , 高通量 DNA测序数据分析方面。 2010获得美国自然科学基金会杰出青年教授奖 (NSF CAREER Award) 。他曾在多个顶极生物信息学国际会议（如 RECOMB, ISMB）的 program committee member，也是 IEEE/ACM Transaction on Computational Biology and Bioinformatics 的 associate editor.
Yufeng Wu is an assistant professor in Computer Science and Engineering Department at University of Connecticut, Storrs, CT, USA. He receives received his PhD degree in Computer Science from University of California, Davis, a Master degree in Computer Science from University of Illinois at Urbana-Champaign in 1998 and Bachelor degree from Tsinghua University, China in 1994. His research interests are in computational biology and bioinformatics. His current work is focused on computational problems in population genomics. He received the Faculty Early Career Development Award from National Science Foundation (NSF CAREER AWARD). He has served in the program committees of leading bioinformatics conferences (e.g. RECOMB and ISMB), and is also an associate editor in IEEE/ACM Transaction on Computational Biology and Bioinformatics.
Selected publications:
1. Y.S. Song, Y. Wu and D. Gusfield, “Efficient computation of close lower and upper bounds on the minimum number of needed recombinations in the evolution of biological sequences", Bioinformatics, Vol.21, Suppl. 1, pp. i413-i422, 2005.
2. Y. Wu, “Association Mapping of Complex Diseases with Ancestral Recombination Graphs: Models and Efficient Algorithms”, Journal of Computational Biology, Vol. 15, No. 7, pp. 667-684, 2008.
3. Y. Wu, “A Practical Method for Exact Computation of Subtree Prune and RegraftDistance ”, Bioinformatics, 25(2): pp. 190-196, 2009.
4. Yufeng Wu, "Computation of Coalescent Likelihood for Panmictic and Subdivided Populations Under the Infinite Sites Model", IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), special issue of ISBRA 2009, 7(4):611-618, 2010.
5. Jin Zhang and Yufeng Wu, "SVseq: an approach for detecting exact breakpoints of deletions with low-coverage sequence data", Bioinformatics, v.27 (23): p. 3228-3234, 2011.
6. Yufeng Wu, "Coalescent-based Species Tree Inference from Gene Tree Topologies Under Incomplete Lineage Sorting by Maximum Likelihood", Evolution, v. 66(3), p. 763-775, 2012.
7. Yufeng Wu: An Algorithm for Constructing Parsimonious Hybridization Networks with Multiple Phylogenetic Trees. RECOMB 2013: 291-303.