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 …
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 …
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 …
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 …
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
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 …
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 …
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
Motivation Computationally predicting major histocompatibility complex class I (MHC-I)
peptide binding affinity is an important problem in immunological bioinformatics, which is …
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
Introduction The comprehensive collection of peptides presented by major histocompatibility
complex (MHC) molecules on the cell surface is collectively known as the …
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
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 …
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 …
vaccine development, but existing methods face limitations such as small datasets, model …