题目：Two fast and accurate biclustering algorithms for analyzing gene expression data

报告人：李国君 教授 （山东大学数学学院）

时间： 7月22日（周三）晚上20:30--21:30

地点：腾讯会议ID：674 966 9522

联系人：杜少飞

Abstract : 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 in gene expression datasets. One is to recognize various trend-preserving biclusters, particularly, those with narrow shapes; the other is to identify various ones, especially, 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.

报告人简历：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年受聘中科院系统科学所研究员，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，担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等。发表学术论文100余篇，其中20多篇发表在 JCTB、Combinatorica、 SIAM J Compt.、Advanced Science、 Genome Biology、 Nucleic Acids Research、 Plos Computational Biology及Bioinformatics等组合数学、算法和生物信息领域的顶级杂志上。另外，两次主持国家基金委的重点项目。

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