MHCPred -- a server for quantitative prediction of peptidex96MHC binding

What you can do:
Quantitatively Predict peptide binding to major histocompatibility complexes (MHC).
  • Accurate T-cell epitope prediction is a principal objective of computational vaccinology.
  • MHCPred is a partial least squares-based multivariate statistical approach to the quantitative prediction of peptide binding to major histocom- patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive cellular immunity.
  • MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401 and HLA-DRB*0701).
  • HLA-A Antigens
  • HLA-DR Antigens
  • major histocom-patibility complexes
  • MHC
  • T-Lymphocyte
  • T-cell
  • T-cell epitope
  • T-cell epitope prediction
  • major histocompatibility complex binding affinity
  • major histocompatibility complex binding affinity prediction
  • MHC binding affinity
  • MHC binding affinity prediction
This record last updated: 08-30-2011
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