Improved method for predicting linear B-cell epitopes JEP Larsen, O Lund, M Nielsen Immunome research 2 (1), 1-7, 2006 | 1141 | 2006 |
Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations M Nielsen, C Lundegaard, P Worning, SL Lauemøller, K Lamberth, ... Protein Science 12 (5), 1007-1017, 2003 | 948 | 2003 |
NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11 C Lundegaard, K Lamberth, M Harndahl, S Buus, O Lund, M Nielsen Nucleic acids research 36 (suppl_2), W509-W512, 2008 | 669 | 2008 |
A generic method for assignment of reliability scores applied to solvent accessibility predictions B Petersen, TN Petersen, P Andersen, M Nielsen, C Lundegaard BMC structural biology 9 (1), 1-10, 2009 | 605 | 2009 |
NetMHCpan, a method for MHC class I binding prediction beyond humans I Hoof, B Peters, J Sidney, LE Pedersen, A Sette, O Lund, S Buus, ... Immunogenetics 61 (1), 1-13, 2009 | 594 | 2009 |
Gapped sequence alignment using artificial neural networks: application to the MHC class I system M Andreatta, M Nielsen Bioinformatics 32 (4), 511-517, 2016 | 544 | 2016 |
Prediction of residues in discontinuous B‐cell epitopes using protein 3D structures P Haste Andersen, M Nielsen, O Lund Protein Science 15 (11), 2558-2567, 2006 | 534 | 2006 |
NetMHCpan-4.0: improved peptide–MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data V Jurtz, S Paul, M Andreatta, P Marcatili, B Peters, M Nielsen The Journal of Immunology 199 (9), 3360-3368, 2017 | 527 | 2017 |
NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and-B locus protein of known sequence M Nielsen, C Lundegaard, T Blicher, K Lamberth, M Harndahl, S Justesen, ... PloS one 2 (8), e796, 2007 | 474 | 2007 |
Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction MV Larsen, C Lundegaard, K Lamberth, S Buus, O Lund, M Nielsen BMC bioinformatics 8 (1), 1-12, 2007 | 469 | 2007 |
NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction M Nielsen, O Lund BMC bioinformatics 10 (1), 1-10, 2009 | 449 | 2009 |
Peptide binding predictions for HLA DR, DP and DQ molecules P Wang, J Sidney, Y Kim, A Sette, O Lund, M Nielsen, B Peters BMC bioinformatics 11 (1), 1-12, 2010 | 445 | 2010 |
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method M Nielsen, C Lundegaard, O Lund BMC bioinformatics 8 (1), 1-12, 2007 | 435 | 2007 |
Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19 T Sekine, A Perez-Potti, O Rivera-Ballesteros, K Strålin, JB Gorin, ... Cell 183 (1), 158-168. e14, 2020 | 409 | 2020 |
The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage M Nielsen, C Lundegaard, O Lund, C Keşmir Immunogenetics 57 (1), 33-41, 2005 | 407 | 2005 |
BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes MC Jespersen, B Peters, M Nielsen, P Marcatili Nucleic acids research 45 (W1), W24-W29, 2017 | 405 | 2017 |
CPHmodels-3.0—remote homology modeling using structure-guided sequence profiles M Nielsen, C Lundegaard, O Lund, TN Petersen Nucleic acids research 38 (suppl_2), W576-W581, 2010 | 389 | 2010 |
Reliable B cell epitope predictions: impacts of method development and improved benchmarking JV Kringelum, C Lundegaard, O Lund, M Nielsen PLoS Comput Biol 8 (12), e1002829, 2012 | 374 | 2012 |
Immune epitope database analysis resource Y Kim, J Ponomarenko, Z Zhu, D Tamang, P Wang, J Greenbaum, ... Nucleic acids research 40 (W1), W525-W530, 2012 | 364 | 2012 |
NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets M Nielsen, M Andreatta Genome medicine 8 (1), 1-9, 2016 | 340 | 2016 |