| 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 B Reynisson, B Alvarez, S Paul, B Peters, M Nielsen Nucleic acids research 48 (W1), W449-W454, 2020 | 1165 | 2020 |
| GibbsCluster: unsupervised clustering and alignment of peptide sequences M Andreatta, B Alvarez, M Nielsen Nucleic acids research 45 (W1), W458-W463, 2017 | 201 | 2017 |
| NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T-cell epitope predictions B Alvarez, B Reynisson, C Barra, S Buus, N Ternette, T Connelley, ... Molecular & Cellular Proteomics 18 (12), 2459-2477, 2019 | 105 | 2019 |
| Footprints of antigen processing boost MHC class II natural ligand predictions C Barra, B Alvarez, S Paul, A Sette, B Peters, M Andreatta, S Buus, ... Genome medicine 10, 1-15, 2018 | 78 | 2018 |
| Computational tools for the identification and interpretation of sequence motifs in immunopeptidomes B Alvarez, C Barra, M Nielsen, M Andreatta Proteomics 18 (12), 1700252, 2018 | 55 | 2018 |
| Accurate MHC motif deconvolution of immunopeptidomics data reveals a significant contribution of DRB3, 4 and 5 to the total DR immunopeptidome S Kaabinejadian, C Barra, B Alvarez, H Yari, WH Hildebrand, M Nielsen Frontiers in Immunology 13, 835454, 2022 | 38 | 2022 |
| NNAlign_MA; semi-supervised MHC peptidome deconvolution for accurate characterization of MHC binding motifs and improved T cell epitope prediction B Alvarez, B Reynisson, C Barra, S Buus, N Ternette, T Connelley, ... bioRxiv, 550673, 2019 | 1 | 2019 |
Morten NielsenDepartment of Health Technology, The Technical University of在 cbs.dtu.dk 的电子邮件经过验证
