IEDB Analysis Resource


Andreatta M. and Nielsen M. 2016. Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics 32:511-7.
PMID: 26515819 Download PDF

Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, and Nielsen M. 2008. NetMHC-3.0: Accurate web accessible predictions of Human, Mouse, and Monkey MHC class I affinities for peptides of length 8-11. NAR 36:W509-512.
PMID: 18463140 Download PDF

Lundegaard C, Nielsen M, Lund O. 2006. The validity of predicted T-cell epitopes. Trends Biotechnol 24:537-538.
PMID: 17045685

Lundegaard C, Lund O, and Nielsen M. 2008. Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers. Bioinformatics 24:1397-1398.
PMID: 18413329

Nielsen M, Lundegaard C, Worning P, Lauemøller SL, Lamberth K, Buus S, Brunak S, Lund O. 2003. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci 12:1007-1017.
PMID: 12717023 Download PDF

Buus S, Lauemøller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J, Holm A, Brunak S. 2003. Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach. Tissue Antigens 62:378-384.
PMID: 14617044

Peters B, Sette A. 2005. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6:132.
PMID: 15927070 Download PDF

Kim Y, Sidney J, Pinilla C, Sette A, Peters B. 2009. Derivation of an amino acid similarity matrix for peptide:MHC binding and its application as a Bayesian prior. BMC Bioinformatics 10:394.
PMID: 19948066 Download PDF

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

Moutaftsi M, Peters B, Pasquetto V, Tscharke DC, Sidney J, Bui HH, Grey H, Sette A. 2006. A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus. Nat Biotechnol 24:817-819.
PMID: 16767078


Jurtz V, Paul S, Andreatta M, Marcatili P, Peters B, Nielsen M. 2017. NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. The Journal of Immunology, 199(9):3360-3368.
PMID: 28978689

Nielsen, M. and Andreatta, M., 2016. NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets. Genome medicine, 8(1), p.33.
PMID: 27029192

Hoof I, Peters B, Sidney J, Pedersen LE, Sette A, Lund O, Buus S, Nielsen M. 2009. NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 61:1-13.
PMID: 19002680 Download PDF

Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, Roder G, Peters B, Sette A, Lund O, Buus S. 2007. NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. PLoS ONE 2:e796.
PMID: 17726526 Download PDF

Links to video presentation on SciVee site: - NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence (paper in Plos One)

Karosiene E, Lundegaard C, Lund O and Nielsen M. 2012. NetMHCcons: a consensus method for the major histocompatibility complex class I predictions. Immunogenetics 64(3):177-186.
PMID: 22009319

Zhang H, Lund O and Nielsen M. 2009. The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC–peptide binding. Bioinformatics 25(10):1293–1299.
PMID: 19297351 Download PDF

Rasmussen, M., Fenoy, E., Harndahl, M., Kristensen, A.B., Nielsen, I.K., Nielsen, M. and Buus, S., 2016. Pan-Specific Prediction of Peptide–MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity. The Journal of Immunology 197(4), pp. 1517-1524.
PMID: 27402703

Population coverage calculations:
Bui H.H., Sidney J., Dinh K., Southwood S., Newman M.J., Sette A. 2006. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics 7:153.
PMID: 16545123

Doolan D.L., Southwood S., Chesnut R., Appella E., Gomez E., Richards A., Higashimoto Y.I., Maewal A., Sidney J., Gramzinski R.A., Mason C., Koech D., Hoffman S.L., Sette A. 2000. HLA-DR-promiscuous T cell epitopes from Plasmodium falciparum pre-erythrocytic-stage antigens restricted by multiple HLA class II alleles. J. Immunol. 165:1123-37.
PMID: 10878392

Meyer D., Singe R.M., Mack S.J., Lancaster A., Nelson M.P., Erlich H., Fernandez-Vina M., Thomson G. 2007. Single Locus Polymorphism of Classical HLA Genes. In Hansen J. (ed.) Immunobiology of the Human MHC: Proceedings of the 13th International Histocompatibility Workshop and Conference. IHWG Press, Seattle.

Gonzalez-Galarza F.F., Christmas S., Middleton D., Jones A.R. 2011. Allele frequency net: a database and online repository for immune gene frequencies in worldwide populations: Nucleic Acid Res. 39:D913-9.
PMID: 21062830

Sette A., Sidney J. 1998. HLA supertypes and supermotifs: a functional perspective on HLA polymorphism. Curr. Opin. Immunol. 10:478-82
PMID: 9722926

Sette A., Sidney J. 1999. Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics 50:201-12
PMID: 10602880

Sidney J., Grey H.M., Kubo R.T., Sette A. 1996. Practical, biochemical and evolutionary implications of the discovery of HLA class I supermotifs. Immunol. Today 17:261-6
PMID: 8962628

Sidney J., Steen A., Moore C., Ngo S., Chung J., Peters B., Sette A. 2010a. Divergent motifs but overlapping binding repertoires of six HLA-DQ molecules frequently expressed in the worldwide human population. J. Immunol. 185:4189-98
PMID: 20810981

Sidney J., Steen A., Moore C., Ngo S., Chung J., Peters B., Sette A. 2010b. Five HLA-DP Molecules Frequently Expressed in the Worldwide Human Population Share a Common HLA Supertypic Binding Specificity. J. Immunol. 184:2492-503
PMID: 20139279

Southwood S., Sidney J., Kondo A., del Guercio M.F., Appella E., Hoffman S., Kubo R.T., Chesnut R.W., Grey H.M., Sette A. 1998. Several common HLA-DR types share largely overlapping peptide binding repertoires. J. Immunol. 160:3363-73
PMID: 9531296

Tiwari J.L., Terasaki P.I. 1985. HLA and disease associations. Springer-Verlag, New York