NetMHCII predicts binding of peptides to HLA-DR, HLA-DQ, HLA-DP and mouse MHC class II alleles using articial neuron networks.
Predictions can be obtained for 14 HLA-DR alleles covering the 9 HLA-DR supertypes, six HLA-DQ, six HLA-DP, and two mouse H2 class II alleles.
The prediction values are given in nM IC50 values, and as a %-Rank to a set of 1,000,000 random natural peptides. Strong and weak binding peptides are indicated in the output.
The server can be run in two modes. Default mode is with P1 amino acids preference. This option is recommended for accurate binding core identification. The other mode excludes P1 amino acids preference encoding, and is turned on selecting the Turn of P1 amino acid preference option. This mode is recommended for accurate binding affinity prediction.
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BMC Bioinformatics. 2009 Sep 18;10:296.
NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.
Nielsen M, Lund O.