AIMC Topic: Histocompatibility Antigens Class I

Clear Filters Showing 1 to 10 of 37 articles

OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

Frontiers in immunology Feb 28, 2025
The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop a novel machine learning framework for predicting antigen peptide presentation by MHC Class I and I...
Peptides Protein Binding Cancer Vaccines Humans Machine Learning Female Endometrial Neoplasms Histocompatibility Antigens Class II Antigen Presentation Vaccine Development Antigens, Neoplasm Histocompatibility Antigens Class I
View on PubMed DOI

VaxOptiML: leveraging machine learning for accurate prediction of MHC-I and II epitopes for optimized cancer immunotherapy.

Immunogenetics Dec 7, 2024
Cancer immunotherapy hinges on accurate epitope prediction for advancing vaccine development. VaxOptiML (available at https://vaxoptiml.streamlit.app/ ) is an integrated pipeline designed to enhance epitope prediction and prioritization. This study a...
Epitopes, T-Lymphocyte Computational Biology Immunotherapy Cancer Vaccines Histocompatibility Antigens Class I Machine Learning Histocompatibility Antigens Class II Software Neoplasms Humans
View on PubMed DOI

Evaluating NetMHCpan performance on non-European HLA alleles not present in training data.

Frontiers in immunology Jan 16, 2024
Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare ap...
Genes, MHC Class I Protein Binding Humans Alleles Peptides Histocompatibility Antigens Class I
View on PubMed DOI

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction.

BMC genomics Nov 23, 2023
Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in...
Deep Learning HLA Antigens Histocompatibility Antigens Class I Humans Neural Networks, Computer Histocompatibility Antigens Class II
View on PubMed DOI

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Analytical biochemistry Feb 3, 2023
Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown that immunotherapy based on non-classical HLA has essential applications in cancer, COVID-19, and allergic diseases. However, there are few deep learnin...
Deep Learning HLA Antigens Histocompatibility Antigens Class I Humans COVID-19 Binding Sites
View on PubMed DOI

DeepSeqPanII: An Interpretable Recurrent Neural Network Model With Attention Mechanism for Peptide-HLA Class II Binding Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
Human leukocyte antigen (HLA) complex molecules play an essential role in immune interactions by presenting peptides on the cell surface to T cells. With significant deep learning progress, a series of neural network-based models have been proposed a...
Histocompatibility Antigens Class I Humans Neural Networks, Computer Peptides Protein Binding HLA Antigens
View on PubMed DOI

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

PLoS computational biology Oct 22, 2021
MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates...
Codon Computational Biology Histocompatibility Antigens Class I Amino Acid Sequence Neural Networks, Computer Algorithms Humans
View on PubMed DOI

T Cell Epitope Prediction and Its Application to Immunotherapy.

Frontiers in immunology Sep 15, 2021
T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for ep...
Immunotherapy Humans Antigens, Neoplasm Base Sequence Neural Networks, Computer Mass Spectrometry Receptors, Antigen, T-Cell Sequence Analysis, DNA Neoplasms Antigen Presentation Computational Biology Epitopes, T-Lymphocyte T-Cell Antigen Receptor Specificity Models, Molecular Peptides Histocompatibility Antigens Class I
View on PubMed DOI

Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics.

Nature communications Jun 7, 2021
Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational...
Humans Peptides Deep Learning Tandem Mass Spectrometry HLA Antigens Ligands Epitopes Extracellular Matrix Proteins Histocompatibility Antigens Class II Proteomics Histocompatibility Antigens Class I Molecular Medicine Mass Spectrometry Cell Line
View on PubMed DOI

DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information.

BMC bioinformatics May 5, 2021
BACKGROUND: Epitope prediction is a useful approach in cancer immunology and immunotherapy. Many computational methods, including machine learning and network analysis, have been developed quickly for such purposes. However, regarding clinical applic...
Epitopes Histocompatibility Antigens Class I Histocompatibility Antigens Class II Deep Learning Protein Binding HLA Antigens Humans Algorithms
View on PubMed DOI
Popular Topics
Recent Journals