For publication of results, please cite:
NetCTL-1.2:
Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction.
Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M.
BMC Bioinformatics. Oct 31;8:424. 2007
View the abstract
NetCTL-1.0:
An integrative approach to CTL epitope prediction.
A combined algorithm integrating MHC-I binding, TAP transport efficiency, and proteasomal cleavage predictions.
Larsen M.V., Lundegaard C., Kasper Lamberth, Buus S,. Brunak S., Lund O., and Nielsen M.
European Journal of Immunology. 35(8): 2295-303. 2005
View the abstract
Reliable prediction of T-cell epitopes using neural networks with novel
sequence representations.
Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S,
Brunak S, Lund O.
Protein Sci., 12:1007-17, 2003.
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Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach.
Buus S, Lauemoller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J, Holm A, Brunak S.
Tissue Antigens., 62(5):378-84, 2003.
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The role of the proteasome in generating cytotoxic T cell epitopes:
Insights obtained from improved predictions of proteasomal cleavage.
M. Nielsen, C. Lundegaard, S. Brunak, O. Lund, and C. Kesmir.
Immunogenetics., 57(1-2):33-41, 2005.
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Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors
Peters, B., Bulik, S., Tampe, R., Endert, P. M. V. and Holzhutter, H. G.
J. Immunol. 171: 1741-1749, 2003.
View the abstract