Version history

• 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.

• 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. https://www.science.org/doi/10.1126/sciadv.adj6367

• 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.

• 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. https://doi.org/10.1038/s42003-023-04749-7

• 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.

• 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

• 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.

• 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

• 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.

• 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

• 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.

• 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

• 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

• User can upload full length MHC class II beta chain and have the server predict MHC restricted peptides from any given protein of interest.

• New concurent algorithm used to train the network.

• %-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.

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.