NetMHC 2.1 Server

NetMHC 2.1 server predicts binding of peptides to a number of different HLA alleles using artificial neural networks (ANNs) and weight matrices.

View the version history of this server. All the previous versions are available on line, for comparison and reference.

Predictions can be obtained for 12 supertypes, and 120 individual alleles using ANNs and weight matrices (ungapped HMMs). ANNs have been trained for 16 different alleles representing 11 HLA supertypes. Weight matrices are generated using a Gibbs sampler approach with data from public databases.

For ANN prediction values are given in nM IC50 values. For weight matrices prediction values are given as a fitness score, so that a high fitness score correlates to strong binding.

For both ANN and weight matrix predictions strong and weak binding peptides are indicated in the output. In the selection window for HLA alleles, the recommended allele for each HLA supertype is indicated.

The project is a collaboration between CBS and IMMI.


Instructions Output format Article abstract


Paste a single sequence or several sequences in FASTA format into the field below:

Submit a file in FASTA format directly from your local disk:

Allele         Sort by affinity 

At most 5000 sequences per submission; each sequence not more than 20,000 amino acids and not less than 9 amino acids.

The sequences are kept confidential and will be deleted after processing.


For publication of results, please cite:

  • Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach.
    Buus S, Lauemoller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J,Holm A, Brunak S.
    Tissue Antigens., 62:378-84, 2003.

    View the abstract or the full text version at PMID: 14617044

  • Reliable prediction of T-cell epitopes using neural networks with novel sequence representations.
    Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S, Brunak S, Lund O.
    Protein Sci., 12:1007-17, 2003.

    View the abstract or the full text version at PMID: 12717023

  • If you specifically use the weight matrix derived predictions, please also cite:

    Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach.
    Nielsen M, Lundegaard C, Worning P, Hvid CS, Lamberth K, Buus S, Brunak S, Lund O.
    Bioinformatics, 20(9):1388-97, 2004.

    View the abstract or the full text version at PMID: 14962912


Would you prefer to run NetMHC at your own site? NetMHC 2.2 is available as a stand-alone software package, with the same functionality as the service above. Ready-to-ship packages exist for the most common UNIX platforms. There is a download page for academic users; other users are requested to contact CBS Software Package Manager at


Scientific problems:        Technical problems: