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 …
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 …
Evaluation of machine learning methods to predict peptide binding to MHC Class I proteins
Binding of peptides to Major Histocompatibility Complex (MHC) proteins is a critical step in
immune response. Peptides bound to MHCs are recognized by CD8+ (MHC Class I) and …
immune response. Peptides bound to MHCs are recognized by CD8+ (MHC Class I) and …
MHCAttnNet: predicting MHC-peptide bindings for MHC alleles classes I and II using an attention-based deep neural model
G Venkatesh, A Grover, G Srinivasaraghavan… - …, 2020 - academic.oup.com
Motivation Accurate prediction of binding between a major histocompatibility complex (MHC)
allele and a peptide plays a major role in the synthesis of personalized cancer vaccines. The …
allele and a peptide plays a major role in the synthesis of personalized cancer vaccines. The …
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 …
MHCSeqNet: a deep neural network model for universal MHC binding prediction
Background Immunotherapy is an emerging approach in cancer treatment that activates the
host immune system to destroy cancer cells expressing unique peptide signatures …
host immune system to destroy cancer cells expressing unique peptide signatures …
DeepMHCII: a novel binding core-aware deep interaction model for accurate MHC-II peptide binding affinity prediction
Motivation Computationally predicting major histocompatibility complex (MHC)-peptide
binding affinity is an important problem in immunological bioinformatics. Recent cutting …
binding affinity is an important problem in immunological bioinformatics. Recent cutting …
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 …
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 …
peptide ligands is important for vaccine design. We introduce an open-source package for …
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 …