报告题目：Genome-wide epistasis analysis

报告人：Erik Aurell（ KTH Sweden）

报告时间：2017年3月24日（星期五） 下午3:00开始

报告地点：主楼1214

报告摘要：

Identifying meaningful pairwise relationships between entities from very high-dimensional data has become a central task in data science. Erik Aurell will describe the approach usually called "direct coupling analysis" (DCA) which has been successfully used to infer residue-residue contacts in proteins and recently also for in-silico protein structure prediction (for a recent state-of-the art, see Ovchinnikov et al, Science 355: 294--298 (2017)). He will give an interpretation of the DCA as an analysis of epistasis, and discuss an application to bacterial genomics. The presentation is based on [MJ Skwark et al. PLoS Genetics vol 13 (2), e1006508 (2017)].

报告人简介：

Erik Aurell is Professor and Chair of Theoretical Biological Physics, Kungliga Tekniska Hogskolan, Stockholm, Sweden and Aalto Adjunct Professor, Aalto University, Finland. In June 10th of 2008, he won Finland Distinguished Academy of Finland Professorship (FiDiPro). He conducts independent research on the frontier of computational biochemistry, bioinformatics, statistical physics and machine learning. He is currently reviewer for PRL, Physical Review, PNAS, and many other scientific journals.