AIMC Topic: Histocompatibility Antigens Class I

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A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes.

Nature communications Mar 12, 2021
Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce the reliability of trans-ethnic major histocompatibility complex (MHC) fine-mapping due to inter-ethn...
Genome-Wide Association Study Genetic Predisposition to Disease Genotype Diabetes Mellitus, Type 1 Humans Deep Learning Racial Groups Linkage Disequilibrium Major Histocompatibility Complex Histocompatibility Antigens Class II HLA Antigens Alleles Histocompatibility Antigens Class I Ethnicity
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TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Computational biology and chemistry Feb 8, 2021
Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Because of the capacity of tumor antigens to activate the immune response and promote the destruction of tumor cells, they are considered excellent immunoth...
Datasets as Topic Humans Machine Learning Algorithms T-Lymphocytes Peptides Computational Biology Antigens, Neoplasm Histocompatibility Antigens Class I
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MATHLA: a robust framework for HLA-peptide binding prediction integrating bidirectional LSTM and multiple head attention mechanism.

BMC bioinformatics Jan 6, 2021
BACKGROUND: Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within personalized T-cell based immunotherapy. Many recent prediction tools developed upon the deep learnin...
Humans Protein Binding Neural Networks, Computer Computational Biology Algorithms Models, Statistical Peptides Histocompatibility Antigens Class I
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Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

Scientific reports Nov 24, 2020
The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cell...
SARS-CoV-2 Epitopes, T-Lymphocyte Peptides COVID-19 Vaccines Humans Machine Learning COVID-19 Histocompatibility Antigens Class I Base Sequence Histocompatibility Antigens Class II Spike Glycoprotein, Coronavirus Computational Biology HLA Antigens Alleles
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Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Cell systems Sep 10, 2020
Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I expos...
Peptides Protein Binding Histocompatibility Antigens Class I Haplotypes Polymorphism, Genetic Viral Proteins Betacoronavirus Humans Neural Networks, Computer SARS-CoV-2
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IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Immunogenetics Jun 24, 2020
Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen...
Amino Acid Sequence Humans Neural Networks, Computer Databases, Protein Computer Simulation Alleles Reproducibility of Results Peptides Histocompatibility Antigens Class I Deep Learning Protein Binding Antigens, Neoplasm
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iTTCA-Hybrid: Improved and robust identification of tumor T cell antigens by utilizing hybrid feature representation.

Analytical biochemistry Apr 22, 2020
In spite of the repertoire of existing cancer therapies, the ongoing recurrence and new cases of cancer poses a challenging health concern that prompts for novel and effective treatment. Cancer immunotherapy represents a promising venue for treatment...
Neoplasms Humans Immunotherapy Machine Learning Antigens, Neoplasm T-Lymphocytes Histocompatibility Antigens Class I
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Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets.

Biochimica et biophysica acta. General subjects Jan 16, 2020
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 models trained on sequence data exist for peptide:MHC (p:MHC) binding...
Animals Peptides Protein Binding Mice Alleles Histocompatibility Antigens Class I Amino Acid Sequence Protein Conformation Machine Learning Algorithms
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High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Cancer immunology research Dec 23, 2019
Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on estimation of MHC binding aff...
Mutation, Missense Histocompatibility Antigens Class II Predictive Value of Tests Histocompatibility Antigens Class I Humans Data Mining Computational Biology Neural Networks, Computer Cancer Vaccines Artificial Intelligence Software Antigens, Neoplasm Algorithms CD8-Positive T-Lymphocytes Neoplasms Protein Binding
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Machine-Learning Prediction of Tumor Antigen Immunogenicity in the Selection of Therapeutic Epitopes.

Cancer immunology research Sep 12, 2019
Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and select for potential epitope targets. These algorithms do not predict for epitope immunogenicity usi...
T-Lymphocytes, Cytotoxic Peptide Fragments Histocompatibility Antigens Class I Histocompatibility Antigens Class II Epitopes, T-Lymphocyte Cancer Vaccines Female Humans Mice Antigens, Neoplasm Animals Machine Learning Mice, Inbred BALB C Computational Biology Male Algorithms Mice, Inbred C57BL Neoplasms
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