PREDmafa: a system for prediction of peptide binding to several MHC class I molecules in cynomolgus macaques
Authors: 
Guang Lan Zhang, Melisa L. Budde, Jennifer J. Lhost, David H. O'Connor, William H. Hildebrand, Vladimir BrusicAuthors Info & Claims
Pages 602 - 606
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, PREDmafa is the first online computational system for predicting peptides that bind Mafa molecules. It is available at http://cvc.dfci.harvard.edu/mafa/.
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Index Terms
- PREDmafa: a system for prediction of peptide binding to several MHC class I molecules in cynomolgus macaques
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Published In
August 2011
688 pages
ISBN:9781450307963
DOI:10.1145/2147805
- General Chairs:
- Robert Grossman,
- Andrey Rzhetsky,
- Program Chairs:
- Sun Kim,
- Wei Wang
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Published: 01 August 2011
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BCB' 11: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine
August 1 - 3, 2011
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