Morten Nielsen

Research.com Recognitions

• 2026 - Research.com Immunology in Denmark Leader Award
• 2025 - Research.com Immunology in Denmark Leader Award
• 2023 - Research.com Immunology in Denmark Leader Award
• 2022 - Research.com Immunology in Denmark Leader Award

Overview

Best Publications

• 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.

  Birkir Reynisson;Bruno Alvarez;Sinu Paul;Bjoern Peters;Bjoern Peters

  2066
  Citations

• Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19.

  Takuya Sekine;André Perez-Potti;Olga Rivera-Ballesteros;Kristoffer Strålin

  1966
  Citations

• BepiPred-2.0: Improving sequence-based B-cell epitope prediction using conformational epitopes

  Martin Closter Jespersen;Bjoern Peters;Morten Nielsen;Paolo Marcatili

  1625
  Citations

• Improved method for predicting linear B-cell epitopes.

  Jens Erik Pontoppidan Larsen;Ole Lund;Morten Nielsen

  1533
  Citations

• NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data

  Vanessa Isabell Jurtz;Sinu Paul;Massimo Andreatta;Paolo Marcatili

  1462
  Citations

• Reliable prediction of T-cell epitopes using neural networks with novel sequence representations

  Morten Nielsen;Claus Lundegaard;Peder Worning;Sanne Lise Lauemøller

  1345
  Citations

• Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

  Massimo Andreatta;Morten Nielsen

  1203
  Citations

• Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

  Mette V Larsen;Claus Lundegaard;Kasper Lamberth;Soren Buus

  1019
  Citations

• NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11

  Claus Lundegaard;Kasper Lamberth;Mikkel Harndahl;Søren Buus

  956
  Citations

• NetMHCpan, a method for MHC class I binding prediction beyond humans

  Ilka Hoof;Bjoern Peters;John Sidney;Lasse Eggers Pedersen

  874
  Citations

• Improved methods for predicting peptide binding affinity to MHC class II molecules

  Kamilla Kjærgaard Jensen;Massimo Andreatta;Paolo Marcatili;Søren Buus

  797
  Citations

• NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.

  Morten A. Nielsen;Claus Lundegaard;Thomas H. Blicher;Kasper Lamberth

  763
  Citations

• Prediction of residues in discontinuous B-cell epitopes using protein 3D structures

  Pernille Haste Andersen;Morten Nielsen;Ole Lund

  756
  Citations

• Peptide binding predictions for HLA DR, DP and DQ molecules

  Peng Wang;John Sidney;Yohan Kim;Alessandro Sette

  750
  Citations

• A generic method for assignment of reliability scores applied to solvent accessibility predictions

  Bent Petersen;Thomas Nordahl Petersen;Pernille Andersen;Pernille Andersen;Morten Nielsen

  737
  Citations

• Reliable B cell epitope predictions: impacts of method development and improved benchmarking.

  Jens Vindahl Kringelum;Claus Lundegaard;Ole Lund;Morten Nielsen

  733
  Citations

• Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

  Morten Nielsen;Claus Lundegaard;Ole Lund

  690
  Citations

• NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.

  Morten Nielsen;Ole Lund

  633
  Citations

• NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning

  Michael Schantz Klausen;Martin Closter Jespersen;Henrik Nielsen;Kamilla Kjærgaard Jensen

  614
  Citations

• The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage

  Morten Nielsen;Claus Lundegaard;Ole Lund;Can Keşmir;Can Keşmir

  600
  Citations

• NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets.

  Morten Nielsen;Massimo Andreatta

  531
  Citations