Author: Morten Nielsen

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Preprints

Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19

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NetTCR: sequence-based prediction of TCR binding to peptide-MHC complexes using convolutional neural networks

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NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data

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

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Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data

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Footprints of antigen processing boost MHC class II natural ligand binding predictions

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NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T cell epitope predictions

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Benchmarking predictions of MHC class I restricted T cell epitopes

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Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes

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A systematic, unbiased mapping of CD8+ and CD4+ T cell epitopes in Yellow Fever vaccinees

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SARS-CoV-2 genome-wide mapping of CD8 T cell recognition reveals strong immunodominance and substantial CD8 T cell activation in COVID-19 patients

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Sampling SARS-CoV-2 proteomes for predicted CD8 T-cell epitopes as a tool for understanding immunogenic breadth and rational vaccine design

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Characterisation of antigenic MHC Class I-restricted T cell epitopes in the glycoprotein of Ebolavirus

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HLA-class II specificity assessed by high-density peptide microarray interactions

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Improved prediction of Bovine Leucocyte Antigens (BoLA) presented ligands by use of MS eluted ligands and in-vitro binding data; impact for the identification T cell epitopes

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Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response

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