What is he best known for?
The fields of study he is best known for:
His scientific interests lie mostly in Epitope, Major histocompatibility complex, Computational biology, Genetics and Peptide binding.
Morten Nielsen has researched Epitope in several fields, including Protein structure, Cytotoxic T cell and Sequence analysis.
His Major histocompatibility complex study incorporates themes from Peptide sequence and Peptide.
His Computational biology study combines topics in areas such as Molecular biology, Plasma protein binding, Immune system and Bioinformatics.
His research investigates the connection with Genetics and areas like Binding selectivity which intersect with concerns in Rhesus macaque.
The concepts of his Peptide binding study are interwoven with issues in HLA-DR, MHC class II and Artificial intelligence.
His most cited work include:
- Improved method for predicting linear B-cell epitopes. (848 citations)
- Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations (760 citations)
- NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11 (556 citations)
What are the main themes of his work throughout his whole career to date?
Morten Nielsen focuses on Epitope, Computational biology, Major histocompatibility complex, Human leukocyte antigen and MHC class I.
In his study, Immunology is strongly linked to Cytotoxic T cell, which falls under the umbrella field of Epitope.
His Computational biology study integrates concerns from other disciplines, such as Immunogenicity, Molecular biology, Sequence motif, In silico and Peptide.
His Major histocompatibility complex study is concerned with the field of Genetics as a whole.
His study brings together the fields of CD8 and Human leukocyte antigen.
His primary area of study in MHC class I is in the field of MHC restriction.
He most often published in these fields:
- Epitope (34.99%)
- Computational biology (29.55%)
- Major histocompatibility complex (26.95%)
What were the highlights of his more recent work (between 2018-2021)?
- Computational biology (29.55%)
- Epitope (34.99%)
- T cell (12.77%)
In recent papers he was focusing on the following fields of study:
His main research concerns Computational biology, Epitope, T cell, Major histocompatibility complex and Immune system.
The Computational biology study combines topics in areas such as Proteome, Immunogenicity, MHC class I, Peptide binding and Peptide.
His Epitope research is within the category of Antigen.
Morten Nielsen usually deals with T cell and limits it to topics linked to Cytotoxic T cell and Immunology, Phenotype and Cancer research.
His study in the field of MHC class II and MHC class II antigen is also linked to topics like Ligand.
His work carried out in the field of Human leukocyte antigen brings together such families of science as In silico and Epitope mapping.
Between 2018 and 2021, his most popular works were:
- Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19. (477 citations)
- NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning (132 citations)
- 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. (124 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Enzyme
- Immune system
His scientific interests lie mostly in Computational biology, Major histocompatibility complex, T cell, Epitope and Antigen presentation.
His research integrates issues of Transcriptome, Genome, Gene, Disease and Omics in his study of Computational biology.
His Major histocompatibility complex study necessitates a more in-depth grasp of Immune system.
His T cell research is multidisciplinary, relying on both Cytotoxic T cell, Ovarian cancer, Tumor-infiltrating lymphocytes and Cell therapy.
His research in Epitope intersects with topics in Receptor, Web server and Set.
His work focuses on many connections between Ligand and other disciplines, such as MHC class II, that overlap with his field of interest in Peptide binding and Antigen processing.
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