Version history

Please click on the version number to activate the corresponding server.

4.3 The current version (online since July 2023). New in this version:
  • NetMHCIIpan-4.3 is trained on an extended dataset of MHC eluted ligands, incorporating new data for HLA-DP, HLA-DR and BoLA-II. Furthermore, an update to the NNAlign_MA machine learning framework allows for prediction of inverted peptide binders.
Main publication:
  • Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning
    Jonas B. Nilsson, Saghar Kaabinejadian, Hooman Yari, Michel G. D. Kester, Peter van Balen, William H. Hildebrand and Morten Nielsen
    Science Advances, 24 Nov 2023.
4.2 (online since September 2022). New in this version:
  • NetMHCIIpan-4.2 is trained on an extensive dataset of both eluted ligand (EL) and binding affinity (BA) data, including new novel EL data for 14 HLA-DQ molecules. Further, a 'distance to training data' metric is printed for each selected molecule in the same way as NetMHCpan-4.1, indicating how reliable the predictions are.
Main publication:
  • Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome
    Jonas Birkelund Nilsson, Saghar Kaabinejadian, Hooman Yari, Bjoern Peters, Carolina Barra, Loren Gragert, William Hildebrand and Morten Nielsen
    Communications Biology, 21 April 2023.
4.1 (online since Sept 2021). New in this version:
  • The method is trained on a extented set of EL data compared to version 4.0, and novel and correct BA for HLA-DQA1*04:01-DQB1*04:02 are included. Further is DRB3, 3 and 5 allele information predicted from DRB1 based on linkage disequilibrium with DRB1 when absent from typing data.
Main publication:

  • Accurate MHC Motif Deconvolution of immunopeptidomics data reveals high relevant contribution of DRB3, 4 and 5 to the total DR Immunopeptidome
    Saghar Kaabinejadian, Carolina Barra, Bruno Alvarez, Hooman Yari, William Hildebrand, Morten Nielsen
    Frontiers in Immunology 26 January 2022. Sec. Antigen Presenting Cell Biology, DOI: 10.3389/fimmu.2022.835454
4.0 (online since April 2020). New in this version:
  • The two output neuron architechture introduced in NetMHCpan-4.0 permits the inclusion of EL data, and the new training algorithm NNAlign_MA extends training data to ligands of ambiguous allele assignments. The model also, optionally, encodes ligand context.
Main publication:

  • Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data.
    Reynisson B, Barra C, Kaabinejadian S, Hildebrand WH, Peters B, Nielsen M
    J Proteome Res 2020 Apr 30. doi: 10.1021/acs.jproteome.9b00874.
    PubMed: 32308001
3.2 (online since January 2018). New in this version:
  • Method retrained on an extensive dataset of over 100,000 datapoints, covering 36 HLA-DR, 27 HLA-DQ, 9 HLA-DP, and 8 mouse MHC-II molecules.
Main publication:

  • Improved methods for predicting peptide binding affinity to MHC class II molecules.
    Jensen KK, Andreatta M, Marcatili P, Buus S, Greenbaum JA, Yan Z, Sette A, Peters B, Nielsen M.
    Immunology. 2018 Jan 6. doi: 10.1111/imm.12889.
    PubMed: 29315598
3.1 (online since December 2014). New in this version:
  • Improved binding core identification by realigning individual networks in the ensemble.
  • Introduced a reliability measure on the predicted binding core (Core_Rel column).
  • Graphical representation of the binding core register and of possible multiple cores.
Main publication:

  • Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification
    Andreatta M, Karosiene E, Rasmussen M, Stryhn A, Buus S, and Nielsen M
    Immunogenetics (2015)
    PubMed: 26416257
3.0 (online since June 2013). New in this version:
  • The user can make predictions for all DR, DP and DQ molecules with known protein sequence. Likewise can the user upload full length MHC class II alpha and beta chain and have the server predict MHC restricted peptides from any given protein of interest
2.1 (online since 6 June 2011). New in this version:
  • User can upload full length MHC class II beta chain and have the server predict MHC restricted peptides from any given protein of interest.
2.0 (online since 17 Nov 2010). New in this version:
  • New concurent algorithm used to train the network.
1.1 (online since 15 April 2010). New in this version:
  • %-rank measure include for each prediction value. The %-rank score give the rank of the prediction score to a distribution of prediction scores from 200.000 natural random 15mer peptides.
1.0 Original version (online version until April 15 2010):

Main publication:

  • Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
    Nielsen M, et al. (2008) PLoS Comput Biol. Jul 4;4(7):e1000107. View the abstract, the full text version at PLoS Compu: Full text.