第387次SKLBE 学术论坛

以下为第387次SKLBE 学术论坛信息，请阅。

报告题目：New development in alignment-free genome and metagenome comparison

报告人：    Fengzhu Sun（孙丰珠）

单位：       University of Southern California, USA

时间：       2017-12-12 10:00-11:30

地点：       18楼315室

主持人：    张立新 研究员

报告人简历和摘要：

孙 丰 珠，博士，教授

美国南加州大学终身教授，博士生导师

2017年Senior Raubenheimer杰出成就奖获得者

 2006-present: Professor of Computational Biology and Bioinformatics

 2007-2015: Head, Computational Biology and Bioinformatics

 2003-2006: Associate Professor, Departments of Biological Sciences and Mathematics

 2000-2003: Associate Professor, Department of Mathematics

Awards and Honors

 2017, USC Dornsife College Senior Raubenheimer Outstanding Achievement Award

 2015, Elected Fellow, American Statistical Association (ASA)

 2012, Elected Fellow, American Association for the Advancement of Sciences (AAAS)

 2012, Elected Member, International Statistical Institute

 2012, Astor Visiting Lectureship Award, Oxford University, UK

 2012, USC Provost’s Mellon Mentoring Award (faculty to faculty), USC

Fengzhu Sun is a Professor of Molecular and Computational Biology. His Bachelors in Mathematics is from Shandong University, Masters in Probability and Statistics is from Peking University, and PhD in Applied Mathematics is from University of Southern California. He came back to USC in 2000 as an associate professor after being an assistant professor of genetics and biostatistics at Emory University from 1995 to 2000. He has been a professor since 2006. Professor Sun works in the area of Computational Biology and Bioinformatics, Statistical Genetics, and Mathematical Modeling. His recent research interests include protein interaction networks, gene expression, single nucleotide polymorphisms (SNP), linkage disequilibrium (LD) and their applications in predicting protein functions, gene regulation networks, and disease gene identification. He is also interested in metagenomics, in particular, marine genomics. His previous research accomplishments include: 1) protein domain interaction and protein function prediction integrating multiple data sources, 2) dynamic programming algorithms for haplotype block partition and tag SNP selection, 3) 1-TDT: transmission disequilibrium test when one parent is available, and 4) theoretical studies of polymerase chain reaction (PCR) related biotechnologies.

报告摘要

Next generation sequencing (NGS) technologies have generated enormous amount of shotgun read data and assembly of the reads is challenging, especially for organisms without reference sequences and metagenomes. We develop novel alignment-free and assembly-free statistics for genome and metagenome comparison. The key idea is to remove the background word counts from the observed counts when comparing genomes and metagenomes. The alignment-free sequence comparison statistics are used to study the relationships among tree species, to assign virus to their hosts, and to classify metagenomes and metatranscriptomes. In all applications, our novel methods yield results that are consistent with biological knowledge. Thus, our statistics provide powerful alternative approaches for genome and metagenome comparison based on NGS short reads.