NetMHCpan - 2.8

Pan-specific binding of peptides to MHC class I alleles of known sequence

NetMHCpan server predicts binding of peptides to any known MHC molecule using artificial neural networks (ANNs). The method is trained on more than 150,000 quantitative binding data covering more than 150 different MHC molecules. Predictions can be made for HLA-A, B, C, E and G alleles, as well as for non-human primates, mouse, Cattle and pig. Further, the user can upload full length MHC protein sequences, and have the server predict MHC restricted peptides from any given protein of interest.

Version 2.8 has been retrained on extented data set including 10 prevalent HLA-C and 7 prevalent BoLA MHC-I molecules.

Predictions can be made for 8-14 mer peptides. Note, that all non 9mer predictions are made using approximations. Most HLA molecules have a strong preference for binding 9mers.

The prediction values are given in nM IC50 values and as %-Rank to a set of 200.000 random natural peptides. For alleles distant to the MHC molecules included in the training of the method, only the Rank score is provided.

The project is a collaboration between CBS, IMMI at Copenhagen University and LIAI.

Link to table (tab seperated) describing the training data Training data table

As of July 8th, the nomenclature for BoLA-I has been updated to follow IPD Release 1.3.


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