Article

Improving generalizability and data efficiency for MHC-I binding peptide predictions through structure-based geometric deep learning

2024-03-26

Abstract excerpt

<title>Abstract</title> <p>The interaction between peptides and major histocompatibility complex (MHC) molecules is pivotal for tissue transplantation, pathogen recognition and autoimmune disease treatments. Recent advances in cancer immunotherapies demand for more accurate computational prediction of MHC-bound peptides. We address the generalizability challenge of MHC-bound peptide predictions, revealing limitat...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b7e3b541-492c-5918-b358-b4c3d6f692e9
DOI: 10.21203/rs.3.rs-3924124/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Improving generalizability and data efficiency for MHC-I binding peptide predictions through structure-based geometric deep learningDOI 10.21203/rs.3.rs-3924124/v1Read

Structure modeling and specificity of peptide-MHC class I interactions using geometric deep learningSemantic proximity Read

MHCSeqNet2-improved peptide-class I MHC binding prediction for alleles with low data.Semantic proximity Read

THLANet: A Deep Learning Framework for Predicting TCR-pHLA Binding in Immunotherapy ApplicationsSemantic proximity Read

SwiftMHC: A High-Speed Attention Network for MHC-Bound Peptide Identification and 3D ModelingSemantic proximity Read

OnionMHC: A Deep Learning Model for Peptide - HLA-A*02:01 Binding Predictions using both Structure and Sequence Feature SetsSemantic proximity Read

Comprehensive evaluation and interpretative insights of peptide-HLA binding prediction tools using explainable artificial intelligenceSemantic proximity Read

MHCBind: A Pan- and Allele-Specific Model for Predicting Class I MHC-Peptide Binding AffinitySemantic proximity Read

TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-xbinding analysesSemantic proximity Read

Deep learning pan-specific model for interpretable MHC-I peptide binding prediction with improved attention mechanism.Semantic proximity Read

STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy featuresSemantic proximity Read

Self-iterative multiple instance learning enables the prediction of CD4 <sup>+</sup> T cell immunogenic epitopesSemantic proximity Read

Designing proteins with reduced T-cell epitopes through policy optimizationSemantic proximity Read