DeepRescore: leveraging deep learning to improve peptide identification in immunopeptidomics
The identification of major histocompatibility complex (MHC)‐binding peptides in mass
spectrometry (MS)‐based immunopeptideomics relies largely on database search engines …
spectrometry (MS)‐based immunopeptideomics relies largely on database search engines …
A community resource benchmarking predictions of peptide binding to MHC-I molecules
Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules
by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a …
by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a …
ACME: pan-specific peptide–MHC class I binding prediction through attention-based deep neural networks
Motivation Prediction of peptide binding to the major histocompatibility complex (MHC) plays
a vital role in the development of therapeutic vaccines for the treatment of cancer. Algorithms …
a vital role in the development of therapeutic vaccines for the treatment of cancer. Algorithms …
Ranking-based convolutional neural network models for peptide-MHC class I binding prediction
T-cell receptors can recognize foreign peptides bound to major histocompatibility complex
(MHC) class-I proteins, and thus trigger the adaptive immune response. Therefore …
(MHC) class-I proteins, and thus trigger the adaptive immune response. Therefore …
Deep learning pan‐specific model for interpretable MHC‐I peptide binding prediction with improved attention mechanism
Accurate prediction of peptide binding affinity to the major histocompatibility complex (MHC)
proteins has the potential to design better therapeutic vaccines. Previous work has shown …
proteins has the potential to design better therapeutic vaccines. Previous work has shown …
Machine learning optimization of peptides for presentation by class II MHCs
T cells play a critical role in cellular immune responses to pathogens and cancer and can be
activated and expanded by Major Histocompatibility Complex (MHC)-presented antigens …
activated and expanded by Major Histocompatibility Complex (MHC)-presented antigens …
An integrated approach for discovering noncanonical MHC-I peptides encoded by small open reading frames
L Chen, Y Zhang, Y Yang, Y Yang, H Li… - Journal of the …, 2021 - ACS Publications
MHC-I peptides are a group of important immunopeptides presented by major
histocompatibility complex (MHC) on the cell surface for immune recognition. The majority of …
histocompatibility complex (MHC) on the cell surface for immune recognition. The majority of …
Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets
MP Aranha, C Spooner, O Demerdash, B Czejdo… - … et Biophysica Acta (BBA …, 2020 - Elsevier
Selecting peptides that bind strongly to the major histocompatibility complex (MHC) for
inclusion in a vaccine has therapeutic potential for infections and tumors. Machine learning …
inclusion in a vaccine has therapeutic potential for infections and tumors. Machine learning …
[HTML][HTML] Immunolyser: A web-based computational pipeline for analysing and mining immunopeptidomic data
PR Munday, J Fehring, J Revote, K Pandey… - Computational and …, 2023 - Elsevier
Immunopeptidomics has made tremendous contributions to our understanding of antigen
processing and presentation, by identifying and quantifying antigenic peptides presented on …
processing and presentation, by identifying and quantifying antigenic peptides presented on …
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 …