MHCPred -- a server for quantitative prediction of peptidex96MHC binding
What you can do:
Quantitatively Predict peptide binding to major histocompatibility complexes (MHC).
Highlights:
- 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).
Keywords:
- 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
Literature & Tutorials:
This record last updated: 08-30-2011