Fw: Fw: 郁彬教授“大学堂”顶尖学者讲学计划-专题讲座二

[z...@amss.ac.cn]

-----原始邮件-----
发件人:"李雷" <li...@amss.ac.cn>
发送时间:2018-05-08 21:02:54 (星期二)
收件人: liqizhai <li...@amss.ac.cn>, "Wan Lin" <lw...@amss.ac.cn>, "Yan Fu" <y...@amss.ac.cn>, "张世华" <z...@amss.ac.cn>, "黎良" <201230...@whu.edu.cn>, "冯伟" <von...@163.com>, "曹晟昊" <5615...@qq.com>, "王博" <flish...@sina.com>, "张升" <zhangshe...@163.com>, "王占宇" <4575...@qq.com>, liyuhan <liyuh...@126.com>
抄送:
主题: Fw: 郁彬教授“大学堂”顶尖学者讲学计划-专题讲座二

-----原始邮件-----
发件人:"北京大学统计科学中心-井天景" <stat-c...@pku.edu.cn>
发送时间:2018-05-08 09:49:35 (星期二)
收件人:
抄送:
主题: 郁彬教授“大学堂”顶尖学者讲学计划-专题讲座二

各位老师好！

    欢迎各位老师参加郁彬教授“大学堂”顶尖学者讲学计划-专题讲座，请自行打印附近入校证，讲座信息如下：

题目：Iterative Random Forests to discover predictive and stable high-order interactions

时间：2018-5-9（星期三） 19:00 ~ 20:30

报告人：Professor Bin Yu, University of California, Berkeley

报告地点：北京大学理教103

摘要：

Genomics has revolutionized biology,enabling the interrogation of whole transcriptomes, genome-wide binding sitesfor proteins, and many other molecular processes. However, individual genomic assays measure elements that interact in vivo as components of larger molecular machines. Understanding how these high-order interactions drive gene expression presents a substantial statistical challenge. Building on random forests (RFs) and random intersection trees (RITs) and through extensive, biologically inspired simulations, we developed the iterative random forest algorithm (iRF). iRF trains a feature-weighted ensemble of decision trees to detect stable,high-order interactions with the same order of computational cost as the RF. We demonstrate the utility of iRF for high-order interaction discovery in two prediction problems: enhancer activity in the early Drosophila embryo and alternative splicing of primary transcripts in human-derived cell lines. In Drosophila, among the 20 pairwise transcription factor interactions iRF identifies as stable (returned in more than half of bootstrap replicates), 80% have been previously reported as physical interactions. Moreover, third-orderinteractions, e.g., between Zelda (Zld), Giant (Gt), and Twist (Twi), sugges thigh-order relationships that are candidates for follow-up experiments. In human-derived cells, iRF rediscovered a central role of H3K36me3 inchromatin-mediated splicing regulation and identified interesting fifth- and sixth-order interactions, indicative of multivalent nucleosomes with specificroles in splicing regulation. By decoupling the order of interactions from the computational cost of identification, iRF opens additional avenues of inquiry into the molecular mechanisms underlying genome biology.

报告人介绍：

郁彬，国际著名统计学家，美国艺术与科学学院院士，美国国家科学院院士。

郁彬教授1984年毕业于北京大学数学系。在2009年到2012年间担任加州大学伯克利分校统计系系主任。郁彬2006年当选Guggenheim Fellow，2012年作了伯努利协会的图基纪念演讲（Tukey Memorial Lecturer）。她还是泛华统计协会2012年首届许宝騄奖的三位获得者之一。她也是AAAS（American Association for the Advancement of Science）、IEEE（Instituteof Electrical and Electronics Engineers）、IMS（Instituteof Mathematical Statistics）和ASA（American Statistical Association）的会士。也曾是2013-2014年度数理统计协会（IMS）主席，并于2013年度当选美国艺术与科学学院（American Academy of Arts and Science）院士，2014年当选美国国家科学院院士。当选院士被认为是美国学术界最高荣誉之一。

郁彬教授在统计理论、高维数据分析、机器学习等方面成绩斐然，享有很高的国际声誉。她对交叉学科研究即广泛又深入。郁彬教授一直关心北大统计学科的发展，先后担任我校的长江讲席教授和千人计划专家（短期项目），指导多名我院青年教师和研究生；是我校统计科学中心科学委员会主任，也是北大微软统计和信息技术实验室的创办者和主任之一，为我校统计学科发展、建设、人才培养做出了巨大贡献。

北京大学统计科学中心