PRED mafa: A system for prediction of peptide binding to several MHC class i molecules in cynomolgus macaques

Guang Lan Zhang, David H. O'Connor, Melisa L. Budde, William H. Hildebrand, Jennifer J. Lhost, Vladimir Brusic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

PREDmafa is a computational system for prediction of peptide binding to three transcriptionally abundant major histocompatibility complex (MHC) class I alleles of Mauritian cynomolgus macaque, an important animal model for the study of human disease. The prediction system utilizes quantitative matrices, which were validated using experimentally determined binders and supported by in vivo studies. We developed 8-mer and 9-mer prediction matrices for Mafa-A1*063:02, 9-mer, 10-mer, and 11-mer prediction matrices for Mafa-B*011:01, and a 9-mer prediction matrix for Mafa-B*075:01. To our knowledge, PRED mafa is the first online computational system for predicting peptides that bind Mafa molecules. It is available at http://cvc.dfci.harvard.edu/mafa/.

Original languageEnglish
Title of host publication2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2011
Pages602-606
Number of pages5
DOIs
Publication statusPublished - Dec 1 2011
Event2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011 - Chicago, IL, United States
Duration: Aug 1 2011Aug 3 2011

Publication series

Name2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2011

Other

Other2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011
CountryUnited States
CityChicago, IL
Period8/1/118/3/11

Keywords

  • HIV
  • MHC
  • Major histocompatibility complex
  • Mauritian cynomolgus macaques
  • Online prediction system
  • SIV
  • Vaccine design

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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