美国佐治亚大学教授学术讲座

    学 术 讲 座

zhong_wenxuan2 (1)主题:Reference-free Learning with Multiple Metagenomic Samples

 

主讲人:Wenxuan Zhong (美国佐治亚大学统计系教授

时间20170705 (周三)上午 10:00-11:30

地点:南开大学津南校区计算机与控制工程学院(信息东楼)523会议室

Abstract The major goals of metagenomics are to identify and study the entire collection of microbial species in a set of targeted samples through sequencing bulk DNA extracted directly from the samples. So far, however, there has not been an effective reference-free tool for dissecting the complex information revealed by the sequencing. In this talk, I will present a statistically based algorithm to simultaneously identify microbial species and estimate their abundances in multiple metagenomic samples without using any reference genome. Compared with existing reference-free methods that are mostly based on k-mer distributions, this new approach can achieve a higher species identification accuracy, and is particularly powerful when the sequencing coverage is low. We demonstrate the performances of the new method through both simulation and real metagenomic studies.

 

 

 

Biography:钟文瑄,现任美国佐治亚大学统计系副教授(Department of Statistics, University of Georgia),大数据分析研究室主任,致力于发展降维方法以及这些方法在机器学习、生物信息等学科问题中的应用,近年来主要研究发展大数据降维的算法及其理论基础。钟文瑄教授本科毕业于南开大学数学系,获美国普渡大学统计学博士,哈佛大学博士后。20078月起,任职于美国伊利诺伊大学香槟分校(University of Illinois at Urbana-Champaign)助理教授2014年被美国佐治亚大学引进. 钟文瑄教授在《Journal of Royal Statistical Society Ser B》,《Journal of American Statistical Association》等国际顶尖期刊上发表多篇论文,形成了极高的影响力。钟文瑄教授的研究被英特尔(Intel)公司,匹兹堡超级计算中心评价为大数据分析的突破性工作;钟文瑄教授担任学术期刊Statistica Sinica等的副主编。