Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, Peters B. 2010. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics. 11:568.
PMID: 21092157

Wang P, Sidney J, Dow C, Mothé B, Sette A, Peters B. 2008. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 4(4):e1000048.
PMID: 18389056

Jensen KK, Andreatta M, Marcatili P, Buus S, Greenbaum JA, Yan Z, Sette A, Peters B, Nielsen M. 2018. Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology 154(3):394-406.
PMID: 29315598

Nielsen M, Lund O. 2009. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction. BMC Bioinformatics. 10:296.
PMID: 19765293

Nielsen M, Lundegaard C, Lund O. 2007. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics. 8:238.
PMID: 17608956

Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A, Peters B. 2008. Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome Res 4:2.
PMID: 18221540

Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, Hammer J. 1999. Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol. 17(6):555-561.
PMID: 10385319

Nilsson JB, Kaabinejadian S, Yari H, Kester MGD, van Balen P, Hildebrand WH, Nielsen M. 2023. Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. Sci Adv.. 9(47):eadj6367. doi: 10.1126/sciadv.adj6367.
PMID: 38000035

Nilsson JB, Kaabinejadian S, Yari H, Peters B, Barra C, Gragert L, Hildebrand W, Nielsen M. 2023. Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome. Commun Biol. 6(1):442. doi: 10.1038/s42003-023-04749-7.
PMID: 37085710

Kaabinejadian S, Barra C, Alvarez B, Yari H, Hildebrand WH, Nielsen M. 2022. Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome. Front Immunol. 13:835454.
PMID: 35154160

Reynisson B., Alvarez B., Paul S., Peters B., Nielsen M. 2020. 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. Nucleic Acids Res. 48(W1):W449-W454.
PMID: 32406916

Jensen KK, Andreatta M, Marcatili P, Buus S, Greenbaum JA, Yan Z, Sette A, Peters B, Nielsen M. 2018. Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology 154(3):394-406.
PMID: 29315598

Andreatta M, Karosiene E, Rasmussen M, Stryhn A, Buus S, and Nielsen M. 2015. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification. Immunogenetics.67(11-12):641-50.
PMID: 26416257