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

yazar

Paolo Marcatili

Morten Nielsen

Sinu Paul

Massimo Andreatta

Bjoern Peters

yayınlandığı: Journal of Immunology

yayımlanma tarihi: 2017-10-04

dil: İngilizce

Cites articles 30

Date

Başlık

Yazarlar

2017-08-23

Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity

David Gfeller, Michal Bassani-Sternberg, Philippe O Gannon, George Coukos
2017-04-20

MuPeXI: prediction of neo-epitopes from tumor sequencing data

Aron Charles Eklund, Anne-Mette Bjerregaard, Morten Nielsen, Sine Reker Hadrup, Zoltan Szallasi
2017-07-01

NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions

Morten Nielsen, Massimo Andreatta
2017-07-01

GibbsCluster: unsupervised clustering and alignment of peptide sequences

Massimo Andreatta, Bruno Alvarez, Morten Nielsen
2017-03-21

MHC-I Ligand Discovery Using Targeted Database Searches of Mass Spectrometry Data: Implications for T-Cell Immunotherapies

Morten Nielsen, Shashi Gujar
2017-02-01

Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction

Nir Hacohen, John Sidney, Siranush Sarkizova
2017-02-01

The problem with neoantigen prediction
2016-11-21

Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

Michal Bassani-Sternberg, Pavel Sinitcyn, Jürgen Cox, Matthias Mann
2016-11-14

MHC class I-associated peptides derive from selective regions of the human genome

Claude Perreault, Pierre Thibault, Chantal Durette, Mathieu Courcelles, Caroline Côté, Sébastien Lemieux, Sylvie Mader, Jean-Philippe Laverdure, Diana Paola Granados, Eric Bonneil
2016-08-10

Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide-HLA Interactions

David Gfeller, Michal Bassani-Sternberg
2016-07-08

Pan-Specific Prediction of Peptide-MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity

Anne Bregnballe Kristensen, Morten Nielsen, Ida Kallehauge Nielsen, Mikkel Harndahl
2016-03-30

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

Massimo Andreatta, Morten Nielsen
2016-01-18

The Length Distribution of Class I-Restricted T Cell Epitopes Is Determined by Both Peptide Supply and MHC Allele-Specific Binding Preference

Thomas Trolle, Morten Nielsen, Alessandro Sette, Bjoern Peters, John Sidney, Curtis McMurtrey, Wilfried Bardet, Thomas Kaever
2015-10-29

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

Morten Nielsen, Massimo Andreatta
2015-09

Tumor neoantigens: building a framework for personalized cancer immunotherapy

Elaine Mardis, Maxim N Artyomov
2015-04-22

Mutant MHC class II epitopes drive therapeutic immune responses to cancer

Mathias Vormehr, Sebastian Boegel, Uğur Şahin, Özlem Türeci, Sebastian Kreiter, Fulvia Vascotto, Mustafa Diken, Christoph Huber, Barbara Schrörs, Martin Löwer, Jan Diekmann, Arbel D Tadmor, Niels van de Roemer
2015-01-09

Mass spectrometry of human leukocyte antigen class I peptidomes reveals strong effects of protein abundance and turnover on antigen presentation

Lars Juhl Jensen, Michal Bassani-Sternberg, Sune Pletscher-Frankild
2014-10-09

The immune epitope database (IEDB) 3.0.

Julia Ponomarenko, Alessandro Sette, Bjoern Peters, Randi Vita, James Overton, Jason A Greenbaum, Jason R Cantrell
2014-01-01

NetMHCstab - predicting stability of peptide-MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery.

Soren Buus, Morten Nielsen
2013-11-04

HLA class I alleles are associated with peptide-binding repertoires of different size, affinity, and immunogenicity

Daniela Weiskopf, Alessandro Sette, Bjoern Peters, John Sidney, Sinu Paul
2013-07-31

NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ.

Morten Nielsen, Ole Lund, Soren Buus, Edita Karosiene
2012-06-01

Peptide-MHC class I stability is a better predictor than peptide affinity of CTL immunogenicity

Morten Nielsen, Mikkel Harndahl
2012-05-25

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

Morten Nielsen
2009-02-04

Peptide binding to HLA class I molecules: homogenous, high-throughput screening, and affinity assays.

Morten Nielsen, Soren Buus, Kasper Lamberth, Sune Justesen
2008-05-07

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

Morten Nielsen, Ole Lund, Mikkel Harndahl, Claus Lundegaard, Soren Buus, Kasper Lamberth
2007-08-29

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

Alessandro Sette, Morten Nielsen, Bjoern Peters, Ole Lund, Mikkel Harndahl, Claus Lundegaard, Soren Buus, Thomas Holberg Blicher, Kasper Lamberth, Sune Justesen
2005-05-01

Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding.

Stefan Tenzer, Hans-Georg Rammensee
2003-05

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

Søren Brunak, Morten Nielsen, Claus Lundegaard, Soren Buus, Kasper Lamberth, Peder Worning, Sanne Lise Lauemøller
2001-05-01

Measurement of MHC/peptide interactions by gel filtration

Alessandro Sette
1992-06-01

Preferred size of peptides that bind to H-2 Kb is sequence dependent

Hidde Ploegh, Ton Schumacher

Makale - wd:Q47696633

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