威廉希尔学术报告
Title：PSISearch2 & protein search platform: Query-seeded iterative sequence similarity searching improves selectivity 20-fold
Speaker：Prof. Wei-Zhong Li,
Sun Yat-sen University
Time：15:30-16:30, Thursday, May 25, 2017
Location：Room 311, Wang Ke-Zhen Building, Peking University
Abstract:
Iterative similarity search programs, like psiblast, jackhmmer, and psisearch, are much more sensitive than pairwise similarity search methods like blast and ssearch because they build a position specific scoring model (a PSSM or HMM) that captures the pattern of sequence conservation characteristic to a protein family. But models are subject to contamination; once an unrelated sequence has been added to the model, homologs of the unrelated sequence will also produce high scores, and the model can diverge from the original protein family. Examination of alignment errors during psiblast PSSM contamination suggested a simple strategy for dramatically reducing PSSM contamination. Psiblast PSSMs are built from the query-based multiple sequence alignment (MSA) implied by the pairwise alignments between the query model (PSSM, HMM) and the subject sequences in the library. When the original query sequence residues are inserted into gapped positions in the aligned subject sequence, the resulting PSSM rarely produces alignment overextensions or alignments to unrelated sequences. This simple step, which tends to anchor the PSSM to the original query sequence and slightly increase target percent identity, can reduce the frequency of false-positive alignments more than 20-fold compared with psiblast and jackhmmer, with little loss in search sensitivity. PSISearch2 is available on our sequence search platform through webform interfaces and RESTful web services.
URLs:
* PSISearch2: http://lilab.sysu.edu.cn/Tools/sss/psisearch2/
* Tools at Li’s lab: http://lilab.sysu.edu.cn/Tools/
* Web service: /index.html
Speaker Bio:
李伟忠，中山大学百人计划2016年国外引进高层次人才，中山大学中山医学院和精准医学科学中心教授、博士生导师，承担国家重点研究计划专项课题（精准医学大数据的整合与注释，2016-2020年）。现任广东生物信息协会副理事长；曾任欧洲生物信息研究所（EMBL-EBI，英国剑桥）生物信息学家/高级软件工程师（2009-2016），北京协和医学院客座教授(2015)，国际核酸联合会（INSDC）欧洲部成员，国际蛋白质联盟 UniProt Consortium 成员，国际分子生物智能系统会员。在 Molecular Systems Biology，P.N.A.S.，Nucleic Acids Research，Bioinformatics等国际权威期刊发表论文共二十多篇，参编专著两部，SCI总引用近2700，Google Scholar总引用超8000 次。担任Nucleic Acids Research，Bioinformatics, Database (Oxford)，The Journal of Gene Medicine 等国际权威期刊评审。
李伟忠参与设计和实施了欧洲生物信息研究所以大数据高性能计算为基础的核心生物信息分析大平台，包括生物信息分析工具框架、大数据获取平台、高通量网络服务平台，服务超过180个国家和地区；建立了全球最完整的生物专利序列数据库；创新性地设计开发的蛋白精确迭代检索引擎PSISearch，新版软件的精确度超过著名同类软件近20倍；深度参与了国际重大生物信息项目，如国际蛋白数据库UniProt、国际核酸数据库 ENA/GenBank、基因组数据库 Ensembl Genomes、多序列比对工具 Clustal Omega、大分子功能注释工具InterProScan，促进了世界范围的生物医学大数据建设和共享。
欢迎各位老师同学积极参加！