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 …

MS‐Rescue: A Computational Pipeline to Increase the Quality and Yield of Immunopeptidomics Experiments

M Andreatta, A Nicastri, X Peng, G Hancock… - …, 2019 - Wiley Online Library
Abstract LC–MS/MS has become the standard platform for the characterization of
immunopeptidomes, the collection of peptides naturally presented by major …

Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction

Y Han, D Kim - BMC bioinformatics, 2017 - Springer
Background Computational scanning of peptide candidates that bind to a specific major
histocompatibility complex (MHC) can speed up the peptide-based vaccine development …

MHCRoBERTa: pan-specific peptide–MHC class I binding prediction through transfer learning with label-agnostic protein sequences

F Wang, H Wang, L Wang, H Lu, S Qiu… - Briefings in …, 2022 - academic.oup.com
Predicting the binding of peptide and major histocompatibility complex (MHC) plays a vital
role in immunotherapy for cancer. The success of Alphafold of applying natural language …

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

B Alvarez, B Reynisson, C Barra, S Buus… - Molecular & Cellular …, 2019 - ASBMB
The set of peptides presented on a cell's surface by MHC molecules is known as the
immunopeptidome. Current mass spectrometry technologies allow for identification of large …

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 …

DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction

W Qu, R You, H Mamitsuka, S Zhu - Bioinformatics, 2023 - academic.oup.com
Motivation Computationally predicting major histocompatibility complex class I (MHC-I)
peptide binding affinity is an important problem in immunological bioinformatics, which is …

The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome

M Nielsen, N Ternette, C Barra - Expert Review of Proteomics, 2022 - Taylor & Francis
Introduction The comprehensive collection of peptides presented by major histocompatibility
complex (MHC) molecules on the cell surface is collectively known as the …

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 …

STMHCpan, an accurate Star-Transformer-based extensible framework for predicting MHC I allele binding peptides

Z Ye, S Li, X Mi, B Shao, Z Dai, B Ding… - Briefings in …, 2023 - academic.oup.com
Peptide-major histocompatibility complex I (MHC I) binding affinity prediction is crucial for
vaccine development, but existing methods face limitations such as small datasets, model …