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Morten Nielsen 0001
Person information
- affiliation: Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark
- affiliation: Universidad Nacional de San Martín, Buenos Aires, Argentina
- affiliation (PhD 1999): McGill University, Department of Physics, Montreal, QC, Canada
Other persons with the same name
- Morten Nielsen — disambiguation page
- Morten Nielsen 0002
— Aalborg University, Department of Mathematical Sciences, Denmark (and 2 more)
- Morten Nielsen 0003
— Technical University of Denmark, Wind Energy Department, Roskilde, Denmark
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2020 – today
- 2024
- [j46]Eve Richardson
, Raphael Trevizani, Jason A. Greenbaum, Hannah Carter, Morten Nielsen, Bjoern Peters:
The receiver operating characteristic curve accurately assesses imbalanced datasets. Patterns 5(6): 100994 (2024) - 2023
- [j45]Daniel Marrama, William D. Chronister, Luise Westernberg, Randi Vita, Zeynep Kosaloglu-Yalçin, Alessandro Sette, Morten Nielsen
, Jason A. Greenbaum, Bjoern Peters:
PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins. BMC Bioinform. 24(1): 485 (2023) - [j44]Zeynep Kosaloglu-Yalçin
, Nina Blazeska, Randi Vita, Hannah Carter, Morten Nielsen
, Stephen Schoenberger, Alessandro Sette, Bjoern Peters:
The Cancer Epitope Database and Analysis Resource (CEDAR). Nucleic Acids Res. 51(D1): 845-852 (2023) - 2022
- [j43]Raphael Trevizani, Zhen Yan, Jason A. Greenbaum, Alessandro Sette, Morten Nielsen
, Bjoern Peters:
A comprehensive analysis of the IEDB MHC class-I automated benchmark. Briefings Bioinform. 23(4) (2022) - [j42]Magnus Haraldson Høie
, Erik Nicolas Kiehl, Bent Petersen
, Morten Nielsen
, Ole Winther
, Henrik Nielsen
, Jeppe Hallgren
, Paolo Marcatili
:
NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning. Nucleic Acids Res. 50(W1): 510-515 (2022) - 2021
- [j41]Jonathan Hare, David Morrison, Morten Nielsen
:
Sampling SARS-CoV-2 Proteomes for Predicted CD8 T-Cell Epitopes as a Tool for Understanding Immunogenic Breadth and Rational Vaccine Design. Frontiers Bioinform. 1 (2021) - 2020
- [j40]Birkir Reynisson, Bruno Alvarez
, Sinu Paul, Bjoern Peters, Morten Nielsen
:
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. 48(Webserver-Issue): W449-W454 (2020) - [j39]Sinu Paul
, Nathan P. Croft
, Anthony W. Purcell
, David C. Tscharke
, Alessandro Sette, Morten Nielsen
, Bjoern Peters
:
Benchmarking predictions of MHC class I restricted T cell epitopes in a comprehensively studied model system. PLoS Comput. Biol. 16(5) (2020)
2010 – 2019
- 2019
- [j38]Emilio Fenoy
, José M. G. Izarzugaza, Vanessa Isabell Jurtz, Søren Brunak, Morten Nielsen
:
A generic deep convolutional neural network framework for prediction of receptor-ligand interactions - NetPhosPan: application to kinase phosphorylation prediction. Bioinform. 35(7): 1098-1107 (2019) - [j37]Swapnil Mahajan
, Zhen Yan, Martin Closter Jespersen, Kamilla Kjærgaard Jensen
, Paolo Marcatili
, Morten Nielsen
, Alessandro Sette, Bjoern Peters:
Benchmark datasets of immune receptor-epitope structural complexes. BMC Bioinform. 20(1): 490:1-490:7 (2019) - [j36]Sandeep Kumar Dhanda
, Swapnil Mahajan
, Sinu Paul, Zhen Yan, Haeuk Kim, Martin Closter Jespersen, Vanessa Isabell Jurtz, Massimo Andreatta
, Jason A. Greenbaum, Paolo Marcatili
, Alessandro Sette, Morten Nielsen
, Bjoern Peters:
IEDB-AR: immune epitope database - analysis resource in 2019. Nucleic Acids Res. 47(Webserver-Issue): W502-W506 (2019) - 2018
- [j35]Massimo Andreatta
, Thomas Trolle
, Zhen Yan, Jason A. Greenbaum, Bjoern Peters, Morten Nielsen
:
An automated benchmarking platform for MHC class II binding prediction methods. Bioinform. 34(9): 1522-1528 (2018) - [j34]Wenguang Shao, Patrick G. A. Pedrioli, Witold Wolski, Christian Scurtescu, Emanuel Schmid
, Juan Antonio Vizcaíno
, Mathieu Courcelles, Heiko Schuster, Daniel Kowalewski, Fabio Marino, Cecilia S. Lindestam Arlehamn
, Kerrie Vaughan, Bjoern Peters, Alessandro Sette, Tom H. M. Ottenhoff, Krista E. Meijgaarden, Natalie Nieuwenhuizen
, Stefan H. E. Kaufmann, Ralph Schlapbach
, John C. Castle, Alexey I. Nesvizhskii, Morten Nielsen
, Eric W. Deutsch, David S. Campbell, Robert L. Moritz, Roman A. Zubarev
, Anders Jimmy Ytterberg, Anthony W. Purcell
, Miguel Marcilla
, Alberto Paradela
, Qi Wang, Catherine E. Costello
, Nicola Ternette
, Peter A. van Veelen
, Cécile A. C. M. van Els, Albert J. R. Heck
, Gustavo A. de Souza, Ludvig Magne Sollid, Arie Admon
, Stefan Stevanovic, Hans-Georg Rammensee, Pierre Thibault, Claude Perreault
, Michal Bassani-Sternberg
, Ruedi Aebersold, Etienne Caron:
The SysteMHC Atlas project. Nucleic Acids Res. 46(Database-Issue): D1237-D1247 (2018) - 2017
- [j33]Diego J. Zea
, Diego Anfossi, Morten Nielsen
, Cristina Marino Buslje
:
MIToS.jl: mutual information tools for protein sequence analysis in the Julia language. Bioinform. 33(4): 564-565 (2017) - [j32]Vanessa Isabell Jurtz, Alexander Rosenberg Johansen, Morten Nielsen
, José Juan Almagro Armenteros
, Henrik Nielsen
, Casper Kaae Sønderby, Ole Winther
, Søren Kaae Sønderby:
An introduction to deep learning on biological sequence data: examples and solutions. Bioinform. 33(22): 3685-3690 (2017) - [j31]Martin Closter Jespersen, Bjoern Peters, Morten Nielsen
, Paolo Marcatili
:
BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 45(Webserver-Issue): W24-W29 (2017) - [j30]Morten Nielsen
, Massimo Andreatta
:
NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions. Nucleic Acids Res. 45(Webserver-Issue): W344-W349 (2017) - [j29]Massimo Andreatta
, Bruno Alvarez
, Morten Nielsen
:
GibbsCluster: unsupervised clustering and alignment of peptide sequences. Nucleic Acids Res. 45(Webserver-Issue): W458-W463 (2017) - 2016
- [j28]Massimo Andreatta
, Morten Nielsen
:
Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinform. 32(4): 511-517 (2016) - 2015
- [j27]Thomas Trolle
, Imir G. Metushi, Jason A. Greenbaum, Yohan Kim, John Sidney, Ole Lund
, Alessandro Sette, Bjoern Peters, Morten Nielsen
:
Automated benchmarking of peptide-MHC class I binding predictions. Bioinform. 31(13): 2174-2181 (2015) - [j26]Michael Schantz Klausen
, Mads Valdemar Anderson
, Martin Closter Jespersen, Morten Nielsen
, Paolo Marcatili
:
LYRA, a webserver for lymphocyte receptor structural modeling. Nucleic Acids Res. 43(Webserver-Issue): W349-W355 (2015) - 2014
- [j25]Yohan Kim, John Sidney, Søren Buus
, Alessandro Sette, Morten Nielsen
, Bjoern Peters:
Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions. BMC Bioinform. 15: 241 (2014) - [c4]Anne Bresciani, Jason Greenbaum, Cecilia S. Lindestam Arlehamn, Alessandro Sette, Morten Nielsen
, Bjoern Peters:
The interplay of sequence conservation and T cell immune recognition. BCB 2014: 739-743 - 2013
- [j24]Massimo Andreatta
, Ole Lund
, Morten Nielsen
:
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach. Bioinform. 29(1): 8-14 (2013) - [j23]Franco L. Simonetti
, Elin Teppa
, Ariel Chernomoretz, Morten Nielsen
, Cristina Marino Buslje
:
MISTIC: mutual information server to infer coevolution. Nucleic Acids Res. 41(Webserver-Issue): 8-14 (2013) - [j22]Leon Eyrich Jessen
, Ilka Hoof
, Ole Lund
, Morten Nielsen
:
SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments. Nucleic Acids Res. 41(Webserver-Issue): 286-291 (2013) - 2012
- [j21]Elin Teppa
, Angela D. Wilkins, Morten Nielsen
, Cristina Marino Buslje
:
Disentangling evolutionary signals: conservation, specificity determining positions and coevolution. Implication for catalytic residue prediction. BMC Bioinform. 13: 235 (2012) - [j20]Martin Christen Frølund Thomsen, Morten Nielsen
:
Seq2Logo: 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. 40(Web-Server-Issue): 281-287 (2012) - [j19]Yohan Kim, Julia V. Ponomarenko
, Zhanyang Zhu, Dorjee Tamang, Peng Wang, Jason Greenbaum, Claus Lundegaard, Alessandro Sette, Ole Lund
, Philip E. Bourne, Morten Nielsen
, Bjoern Peters:
Immune epitope database analysis resource. Nucleic Acids Res. 40(Web-Server-Issue): 525-530 (2012) - [j18]Jens Vindahl Kringelum, Claus Lundegaard, Ole Lund
, Morten Nielsen
:
Reliable B Cell Epitope Predictions: Impacts of Method Development and Improved Benchmarking. PLoS Comput. Biol. 8(12) (2012) - 2010
- [j17]Peng Wang
, John Sidney, Yohan Kim, Alessandro Sette, Ole Lund
, Morten Nielsen
, Björn Peters:
Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinform. 11: 568 (2010) - [j16]Morten Nielsen
, Claus Lundegaard, Ole Lund
, Thomas Nordahl Petersen
:
CPHmodels-3.0 - remote homology modeling using structure-guided sequence profiles. Nucleic Acids Res. 38(Web-Server-Issue): 576-581 (2010) - [j15]Cristina Marino Buslje
, Elin Teppa
, Tomás Di Domenico
, José María Delfino, Morten Nielsen
:
Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification. PLoS Comput. Biol. 6(11) (2010) - [c3]Claus Lundegaard, M. Buggert, A. C. Karlsson, Ole Lund, Carina Perez, Morten Nielsen:
PopCover: a method for selecting of peptides with optimal population and pathogen coverage. BCB 2010: 658-659
2000 – 2009
- 2009
- [j14]Hao Zhang, Claus Lundegaard, Morten Nielsen
:
Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods. Bioinform. 25(1): 83-89 (2009) - [j13]Cristina Marino Buslje
, Javier Santos
, José María Delfino, Morten Nielsen
:
Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information. Bioinform. 25(9): 1125-1131 (2009) - [j12]Hao Zhang, Ole Lund
, Morten Nielsen
:
The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding. Bioinform. 25(10): 1293-1299 (2009) - [j11]Morten Nielsen
, Ole Lund
:
NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction. BMC Bioinform. 10: 296 (2009) - 2008
- [j10]Claus Lundegaard, Ole Lund
, Morten Nielsen
:
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. 24(11): 1397-1398 (2008) - [j9]Claus Lundegaard, Kasper Lamberth, Mikkel Harndahl, Søren Buus
, Ole Lund
, Morten Nielsen
:
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. 36(Web-Server-Issue): 509-512 (2008) - [j8]Qing Zhang, Peng Wang, Yohan Kim, Pernille Haste-Andersen, John E. Beaver, Philip E. Bourne, Huynh-Hoa Bui, Søren Buus
, Sune Frankild
, Jason Greenbaum, Ole Lund
, Claus Lundegaard, Morten Nielsen
, Julia V. Ponomarenko
, Alessandro Sette, Zhanyang Zhu, Björn Peters:
Immune epitope database analysis resource (IEDB-AR). Nucleic Acids Res. 36(Web-Server-Issue): 513-518 (2008) - [j7]Morten Nielsen
, Claus Lundegaard, Thomas Blicher, Bjoern Peters, Alessandro Sette, Sune Justesen, Søren Buus
, Ole Lund
:
Quantitative Predictions of Peptide Binding to Any HLA-DR Molecule of Known Sequence: NetMHCIIpan. PLoS Comput. Biol. 4(7) (2008) - 2007
- [j6]Claus Lundegaard, Ole Lund
, Can Kesmir, Søren Brunak
, Morten Nielsen
:
Modeling the adaptive immune system: predictions and simulations. Bioinform. 23(24): 3265-3275 (2007) - [j5]Mette V. Larsen, Claus Lundegaard, Kasper Lamberth, Søren Buus
, Ole Lund
, Morten Nielsen
:
Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinform. 8 (2007) - [j4]Morten Nielsen
, Claus Lundegaard, Ole Lund
:
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinform. 8 (2007) - 2006
- [j3]Bjoern Peters, Huynh-Hoa Bui, Sune Frankild
, Morten Nielsen
, Claus Lundegaard, Emrah Kostem, Derek Basch, Kasper Lamberth, Mikkel Harndahl, Ward Fleri
, Stephen S. Wilson, John Sidney, Ole Lund
, Søren Buus
, Alessandro Sette:
A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules. PLoS Comput. Biol. 2(6) (2006) - 2005
- [b1]Ole Lund, Morten Nielsen, Claus Lundegaard, Can Kesmir, Søren Brunak:
Immunological bioinformatics. Computational molecular biology, AAAI Press 2005, ISBN 978-0-262-12280-1, pp. I-XII, 1-296 - 2004
- [j2]Morten Nielsen
, Claus Lundegaard, Peder Worning, Christina Sylvester-Hvid, Kasper Lamberth, Søren Buus
, Søren Brunak
, Ole Lund
:
Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach. Bioinform. 20(9): 1388-1397 (2004) - [c2]Claus Lundegaard, Morten Nielsen, Kasper Lamberth, Peder Worning, Christina Sylvester-Hvid, Søren Buus, Søren Brunak, Ole Lund
:
MHC Class I Epitope Binding Prediction Trained on Small Data Sets. ICARIS 2004: 217-225 - 2003
- [j1]Jens Kaae Christensen, Kasper Lamberth, Morten Nielsen
, Claus Lundegaard, Peder Worning, Sanne Lise Lauemøller, Søren Buus
, Søren Brunak
, Ole Lund
:
Selecting Informative Data for Developing Peptide-MHC Binding Predictors Using a Query by Committee Approach. Neural Comput. 15(12): 2931-2942 (2003) - [c1]Claus Lundegaard, Thomas Nordahl Petersen, Morten Nielsen, Henrik Bohr, Jakob Bohr, Søren Brunak, Garry Gippert, Ole Lund:
Prediction of Protein Secondary Structure at High Accuracy Using a Combination of Many Neural Networks. Mathematical Methods for Protein Structure Analysis and Design 2003: 117-122
Coauthor Index
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last updated on 2024-08-05 20:22 CEST by the dblp team
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