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NetMHCpan 4.1b

The NetMHCpan-4.1 server predicts binding of peptides to any MHC molecule of known sequence using artificial neural networks (ANNs). The method is trained on a combination of more than 850,000 quantitative Binding Affinity (BA) and Mass-Spectrometry Eluted Ligands (EL) peptides. The BA data covers 201 MHC molecules from human (HLA-A, B, C, E), mouse (H-2), cattle (BoLA), primates (Patr, Mamu, Gogo), swine (SLA) and equine (Eqca). The EL data covers 289 MHC molecules from human (HLA-A, B, C, E), mouse (H-2), cattle (BoLA), primates (Patr, Mamu, Gogo), swine (SLA), equine (Eqca) and dog (DLA). Furthermore, the user can obtain predictions to any custom MHC class I molecule by uploading a full length MHC protein sequence. Predictions can be made for peptides of any length.

Note, as of 28/7/2020 the server has been updated (retrained on data resolving a curation error in the IEDB for a single allele (SA) eluted ligand H2-Db/H2-Kb data set. This recuration only affected ~2000 H2 data points, but has minor impacts on predictions for all MHC's.

To access the earlier version of NetMHCpan-4.1 click here version 4.1a

Note also, if you have installed the earlier version of NetMHCpan-4.1, click here to download the updated data file data.tar.gz, and a file with the update test directory test.tar.gz.

The server returns as default the likelihood of a peptide being a natural ligand of the selected MHC(s). If selected, also the predicted binding affinity is rseported.

New in this version: together with Binding Affinity (BA) data, the method has now been trained on EL data from Single Allele (SA, peptides annotated to a single MHC) and Multi Allele (MA, peptides annotated to multiple MHCs) sources. The use of EL MA data is possible due to an upgrade af NNAlign (the core algorithm of NetMHCpan) called NNALign_MA (PMID: 31578220), which enables pseudo-labelling.

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

The project is a collaboration between DTU Bioinformatics, and LIAI.


Instructions Output format Motif viewer Article abstract Training and Evaluation Data sets

SUBMISSION

Hover the mouse cursor over the symbol for a short description of the options

INPUT TYPE:

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

... or upload a file in FASTA format directly from your local disk:

... or load some sample data:



PEPTIDE LENGTH:  

You may select multiple lengths


SELECT SPECIES/LOCI:



Select Allele(s) (max 20 per submission)


... or type Allele names (i.e. HLA-A01:01) separated by commas and without spaces (max 20 per submission): 

For a list of allowed allele names click here

... or paste a single full length MHC protein sequence in FASTA format into the field below:

... or load a file containing a full length MHC protein sequence in FASTA format directly from your local disk:



ADDITIONAL CONFIGURATION:

Threshold for strong binder: % Rank 

Threshold for weak binder: % Rank 

Filtering threshold for %Rank (leave -99 to print all) 

Include BA predictions  

Sort by prediction score 

Save predictions to XLS file 





Restrictions:
At most 5000 sequences per submission; each sequence not more than 20,000 amino acids and not less than 8 amino acids. Max 20 MHC alleles per submission.

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


CITATIONS

For publication of results, please cite:

  • This version: NetMHCpan-4.1 and NetMHCIIpan-4.0: Improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data
    Birkir Reynisson, Bruno Alvarez, Sinu Paul, Bjoern Peters and Morten Nielsen
    Nucleic Acids Research, May 2020, https://doi.org/10.1093/nar/gkaa379 Full text
  • NetMHCpan-4.0: Improved Peptide MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data
    Vanessa Jurtz, Sinu Paul, Massimo Andreatta, Paolo Marcatili, Bjoern Peters and Morten Nielsen
    The Journal of Immunology (2017) ji1700893; DOI: 10.4049/jimmunol.1700893
    Full text   [PDF]
  • NetMHCpan-3.0: improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length data sets
    Morten Nielsen and Massimo Andreatta
    Genome Medicine (2016): 8:33
    Full text   [PDF]
  • NetMHCpan, a method for MHC class I binding prediction beyond humans
    Ilka Hoof, Bjoern Peters, John Sidney, Lasse Eggers Pedersen, Ole Lund, Soren Buus, and Morten Nielsen
    Immunogenetics 61.1 (2009): 1-13
    PMID: 19002680   Full text

DATA RESOURCES

Data resources used to develop this server was obtained from

  • IEDB database.
    • Quantitative peptide binding data were obtained from the IEDB database.
  • IMGT/HLA database. Robinson J, Malik A, Parham P, Bodmer JG, Marsh SGE: IMGT/HLA - a sequence database for the human major histocompatibility complex. Tissue Antigens (2000), 55:280-287.
    • HLA protein sequences were obtained from the IMGT/HLA database (version 3.1.0).

PORTABLE VERSION

Would you prefer to run NetMHCpan at your own site? NetMHCpan v. 4.1 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 software@cbs.dtu.dk.


GETTING HELP

Scientific problems:        Technical problems: