Morten Nielsen
Orcid: 0000-0001-7885-4311Affiliations:
- Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark
- Universidad Nacional de San Martín, Buenos Aires, Argentina
- McGill University, Department of Physics, Montreal, QC, Canada (PhD 1999)
According to our database1,
Morten Nielsen
authored at least 51 papers
between 2003 and 2024.
Collaborative distances:
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Bibliography
2024
Patterns, 2024
2023
PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins.
BMC Bioinform., December, 2023
Nucleic Acids Res., January, 2023
2022
NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning.
Nucleic Acids Res., 2022
Briefings Bioinform., 2022
2021
Sampling SARS-CoV-2 Proteomes for Predicted CD8 T-Cell Epitopes as a Tool for Understanding Immunogenic Breadth and Rational Vaccine Design.
Frontiers Bioinform., 2021
2020
Benchmarking predictions of MHC class I restricted T cell epitopes in a comprehensively studied model system.
PLoS Comput. Biol., 2020
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.
Nucleic Acids Res., 2020
2019
Nucleic Acids Res., 2019
BMC Bioinform., 2019
A generic deep convolutional neural network framework for prediction of receptor-ligand interactions - NetPhosPan: application to kinase phosphorylation prediction.
Bioinform., 2019
2018
Bioinform., 2018
2017
BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes.
Nucleic Acids Res., 2017
Nucleic Acids Res., 2017
NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions.
Nucleic Acids Res., 2017
MIToS.jl: mutual information tools for protein sequence analysis in the Julia language.
Bioinform., 2017
An introduction to deep learning on biological sequence data: examples and solutions.
Bioinform., 2017
2016
Gapped sequence alignment using artificial neural networks: application to the MHC class I system.
Bioinform., 2016
2015
Nucleic Acids Res., 2015
2014
Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions.
BMC Bioinform., 2014
Proceedings of the 5th ACM Conference on Bioinformatics, 2014
2013
<i>SigniSite</i>: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments.
Nucleic Acids Res., 2013
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
Bioinform., 2013
2012
Reliable B Cell Epitope Predictions: Impacts of Method Development and Improved Benchmarking.
PLoS Comput. Biol., 2012
<i>Seq2Logo</i>: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion.
Nucleic Acids Res., 2012
Disentangling evolutionary signals: conservation, specificity determining positions and coevolution. Implication for catalytic residue prediction.
BMC Bioinform., 2012
2010
Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification.
PLoS Comput. Biol., 2010
Nucleic Acids Res., 2010
PopCover: a method for selecting of peptides with optimal population and pathogen coverage.
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, 2010
2009
<i>NN-align</i>. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.
BMC Bioinform., 2009
The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding.
Bioinform., 2009
Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods.
Bioinform., 2009
Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information.
Bioinform., 2009
2008
Quantitative Predictions of Peptide Binding to Any HLA-DR Molecule of Known Sequence: NetMHCIIpan.
PLoS Comput. Biol., 2008
NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.
Nucleic Acids Res., 2008
Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers.
Bioinform., 2008
2007
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.
BMC Bioinform., 2007
BMC Bioinform., 2007
2006
PLoS Comput. Biol., 2006
2005
Immunological bioinformatics.
Computational molecular biology, AAAI Press, ISBN: 978-0-262-12280-1, 2005
2004
Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach.
Bioinform., 2004
Proceedings of the Artificial Immune Systems, Third International Conference, 2004
2003
Selecting Informative Data for Developing Peptide-MHC Binding Predictors Using a Query by Committee Approach.
Neural Comput., 2003
Prediction of Protein Secondary Structure at High Accuracy Using a Combination of Many Neural Networks.
Proceedings of the Mathematical Methods for Protein Structure Analysis and Design, 2003