IEDB Analysis Resource

References

ANN:
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

SMM:
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

SMMPMBEC:
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

CombLib:
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

Consensus:
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

NetMHCpan:

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 Download PDF

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:
http://www.scivee.tv/node/4651 - NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence (paper in Plos One)

NetMHCcons:
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

PickPocket:
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

NetMHCstabpan:
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