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

V Jurtz, S Paul, M Andreatta, P Marcatili… - The Journal of …, 2017 - journals.aai.org
Cytotoxic T cells are of central importance in the immune system's response to disease.
They recognize defective cells by binding to peptides presented on the cell surface by MHC …

[HTML][HTML] MHCflurry 2.0: improved pan-allele prediction of MHC class I-presented peptides by incorporating antigen processing

TJ O'Donnell, A Rubinsteyn, U Laserson - Cell systems, 2020 - cell.com
Computational prediction of the peptides presented on major histocompatibility complex
(MHC) class I proteins is an important tool for studying T cell immunity. The data available to …

[HTML][HTML] A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach

P Wang, J Sidney, C Dow, B Mothé… - PLoS computational …, 2008 - journals.plos.org
The identification of MHC class II restricted peptide epitopes is an important goal in
immunological research. A number of computational tools have been developed for this …

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

M Nielsen, M Andreatta - Genome medicine, 2016 - Springer
Background Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen
presentation to cytotoxic T-cells. Results Here, we demonstrate how a simple alignment step …

NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand …

B Reynisson, B Alvarez, S Paul, B Peters… - Nucleic acids …, 2020 - academic.oup.com
Major histocompatibility complex (MHC) molecules are expressed on the cell surface, where
they present peptides to T cells, which gives them a key role in the development of T-cell …

[HTML][HTML] Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS computational biology, 2018 - journals.plos.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Improved methods for predicting peptide binding affinity to MHC class II molecules

KK Jensen, M Andreatta, P Marcatili, S Buus… - …, 2018 - Wiley Online Library
Major histocompatibility complex class II (MHC‐II) molecules are expressed on the surface
of professional antigen‐presenting cells where they display peptides to T helper cells, which …

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

B Reynisson, C Barra, S Kaabinejadian… - Journal of proteome …, 2020 - ACS Publications
Major histocompatibility complex II (MHC II) molecules play a vital role in the onset and
control of cellular immunity. In a highly selective process, MHC II presents peptides derived …

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

M Andreatta, E Karosiene, M Rasmussen, A Stryhn… - Immunogenetics, 2015 - Springer
A key event in the generation of a cellular response against malicious organisms through
the endocytic pathway is binding of peptidic antigens by major histocompatibility complex …

[HTML][HTML] MHCflurry: open-source class I MHC binding affinity prediction

TJ O'Donnell, A Rubinsteyn, M Bonsack, AB Riemer… - Cell systems, 2018 - cell.com
Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their
peptide ligands is important for vaccine design. We introduce an open-source package for …