10-21SystematicandIntegrativeBioinformaticCollection,Representation,andAnalysisofVaccinesandPathogenVirulenceFactors
发布时间 :2016-10-19  阅读次数 :5770

报告题目:Systematic and Integrative Bioinformatic Collection, Representation, and Analysis of Vaccines and Pathogen Virulence Factors

报  告 人:Dr. Yongqun He, Associate Professor

Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, University of Michigan Medical School

报告时间:10月21日 9:30-10:30

报告地点:徐汇校区(Xuhui Campus)哲生馆101会议室

联  系 人: 欧竑宇 This e-mail address is being protected from spambots. You need JavaScript enabled to view it.

 

Abstract:

Bioinformatics has been extensively used to study vaccines and virulence factors. This talk will introduce three topics in the area of bioinformatics studies on vaccines and virulence factors. First, I will introduce the comprehensive web-based VIOLIN vaccine database system (http://www.violinet.org). VIOLIN includes Vaxign, the first web-based reverse vaccinology software program. The predicted features in Vaxign include antigen subcellular location, adhesin, epitope binding to MHC class I and class II, and sequence similarities to host proteins. VIOLIN also includes many individual databases for collecting manually curated data related to different vaccine components, such as Protegen for vaccine protective antigens, Vaxjo for vaccine adjuvants, Vaxvec for vaccine vectors, and DNAVaxDB for DNA vaccines. Second, I will introduce the web-based virulence factor database Victors (http://www.phidias.us/victors).  Victors have collected and analyzed over 5,000 virulence factors from over 100 bacteria, viruses, parasites, and fungi. Analysis of these virulence factors has identified interesting scientific insights. Third, I will introduce how ontology can be used to study vaccines and virulence factors. The Vaccine Ontology (VO) and the Ontology of Host-Pathogen Interactions (OHPI) have been developed to semantically represent vaccines, virulence factors, and their related information. The usage of VO, OHPI and other related ontologies has significantly supported data and knowledge integration, systematic analysis, and scientific discovery.