Improved method for predicting linear B-cell epitopes JEP Larsen, O Lund, M Nielsen Immunome research 2 (1), 2, 2006 | 950 | 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 | 781 | 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 | 573 | 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), 51, 2009 | 539 | 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, 2009 | 490 | 2009 |
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 | 456 | 2006 |
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 | 408 | 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), 296, 2009 | 367 | 2009 |
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), 238, 2007 | 359 | 2007 |
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), 568, 2010 | 342 | 2010 |
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 | 338 | 2010 |
Gapped sequence alignment using artificial neural networks: application to the MHC class I system M Andreatta, M Nielsen Bioinformatics 32 (4), 511-517, 2015 | 324 | 2015 |
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 (1-2), 33-41, 2005 | 324 | 2005 |
A community resource benchmarking predictions of peptide binding to MHC-I molecules B Peters, HH Bui, S Frankild, M Nielsen, C Lundegaard, E Kostem, ... PLoS computational biology 2 (6), e65, 2006 | 301 | 2006 |
Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach M Nielsen, C Lundegaard, P Worning, CS Hvid, K Lamberth, S Buus, ... Bioinformatics 20 (9), 1388-1397, 2004 | 300 | 2004 |
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), 424, 2007 | 296 | 2007 |
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 | 284 | 2012 |
An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions MV Larsen, C Lundegaard, K Lamberth, S Buus, S Brunak, O Lund, ... European journal of immunology 35 (8), 2295-2303, 2005 | 273 | 2005 |
Definition of supertypes for HLA molecules using clustering of specificity matrices O Lund, M Nielsen, C Kesmir, AG Petersen, C Lundegaard, P Worning, ... Immunogenetics 55 (12), 797-810, 2004 | 259 | 2004 |
Reliable B cell epitope predictions: impacts of method development and improved benchmarking JV Kringelum, C Lundegaard, O Lund, M Nielsen PLoS computational biology 8 (12), e1002829, 2012 | 257 | 2012 |