报告题目: Algorithms for biclustering gene expression data
报告人:李国君 教授,山东大学
报告摘要:Biclustering has emerged as a powerful approach to identifying functional patterns in complex biological data. However, existing tools are limited by their accuracy and efficiency to recognize various kinds of complex biclusters submerged in ever large datasets. We introduce two novel biclustering algorithms, which are complementary, to identify all the most meaningful local structures, so-called trend-preserving biclusters, in gene expression datasets. One prefers these with narrow shapes, and the other those with broader shapes. Tested on both simulated and real datasets, they substantially outperformed all the compared salient tools in terms of accuracy and robustness to noise and overlaps between the clusters.
报告人简介:李国君,教授,1996年获中科院数学与系统科学研究院博士学位,1995年晋升教授,2000年担任博士生导师,2004-2005年受聘中科院软件所研究员,2006年受聘美国佐治亚大学资深研究教授,2005年获批山东省“泰山学者”特聘教授,2014年全职回国工作,现任山东大学特聘教授。他的研究领域涉及图论、计算机科学和生物信息等。代表性工作包括:证明了Chvátal猜想为代表的4个图论猜想;解决了两个长期争议的可近似性问题;突破了数个生物数据挖掘的算法瓶颈。发表学术论文100余篇,其中以主要作者在组合数学、算法理论和生物信息学领域的顶级杂志上发表论文20多篇,包括JCTB 1篇、Combinatorica 1篇、SIAM J Compt. 1篇、ACM Trans. Algorithms 2篇、Advanced Science 2篇、Genome Biology 3篇、Nucleic Acids Research 6篇、Plos Computational Biology 1篇、Bioinformatics 4篇。另外,两次主持国家基金委的重点项目。
报告邀请人:图论组合优化团队
报告时间:2020年8月3日(周一)9:00-10:00
报告地点:腾讯会议 ID: 663255147