AIMC Topic: Epitopes

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and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

The Journal of biological chemistry May 23, 2017
Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-s...
Humans Artificial Intelligence Cells, Cultured Melanoma Antigens, Neoplasm Vaccines, Synthetic Membrane Proteins Neoplasm Proteins Reproducibility of Results Animals Computational Biology Cancer Vaccines Immunogenicity, Vaccine Mice, Transgenic Models, Immunological Protein Refolding T-Lymphocytes, Cytotoxic HLA-A2 Antigen Protein Stability Expert Systems Oligopeptides Mice, Knockout Peptide Fragments Epitopes
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Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology.

International journal of molecular sciences Feb 1, 2017
Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of...
Bacterial Vaccines Epitope Mapping Vaccines, Subunit ROC Curve Computational Biology Support Vector Machine Area Under Curve Bacterial Proteins Epitopes Mutagenesis Antigens, Bacterial Humans Machine Learning
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Improved pan-specific prediction of MHC class I peptide binding using a novel receptor clustering data partitioning strategy.

HLA Oct 20, 2016
Pan-specific prediction of receptor-ligand interaction is conventionally done using machine-learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing ...
Gorilla gorilla Pan troglodytes Protein Interaction Domains and Motifs Structural Homology, Protein Macaca Mice Gene Expression Epitopes Alleles Histocompatibility Antigens Class I Ligands Machine Learning Oligopeptides Software Binding Sites Animals Humans Protein Binding
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An ontology for major histocompatibility restriction.

Journal of biomedical semantics Jan 11, 2016
BACKGROUND: MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in ...
Humans Software Animals Gene Ontology Databases, Protein Major Histocompatibility Complex HLA Antigens Histocompatibility Antigens Epitopes
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Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

Bioinformatics (Oxford, England) Oct 29, 2015
MOTIVATION: Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to pep...
Histocompatibility Antigens Class I Sequence Alignment Protein Binding Computational Biology Peptide Fragments Epitopes Humans Neural Networks, Computer Algorithms
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Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

Immunogenetics Sep 29, 2015
A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented ...
Mice Binding Sites Computational Biology Humans Algorithms Molecular Sequence Data Cluster Analysis Models, Molecular Neural Networks, Computer Sequence Homology, Amino Acid Peptide Fragments Databases, Protein Animals Histocompatibility Antigens Class II Epitopes Protein Binding Amino Acid Sequence
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High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England) Jul 23, 2015
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...
Databases, Protein Peptides ROC Curve Area Under Curve Molecular Sequence Data Humans Protein Binding Epitopes Support Vector Machine Neural Networks, Computer Major Histocompatibility Complex Amino Acid Sequence Algorithms
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Geometric epitope and paratope prediction.

Bioinformatics (Oxford, England) Jul 1, 2024
MOTIVATION: Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the ...
Antibodies Epitopes Protein Conformation Binding Sites Software Deep Learning Computational Biology
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HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

Briefings in bioinformatics May 23, 2024
While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identifica...
Epitopes, T-Lymphocyte Deep Learning Computational Biology Epitopes Histocompatibility Antigens Class II Humans
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PiTE: TCR-epitope Binding Affinity Prediction Pipeline using Transformer-based Sequence Encoder.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2023
Accurate prediction of TCR binding affinity to a target antigen is important for development of immunotherapy strategies. Recent computational methods were built on various deep neural networks and used the evolutionary-based distance matrix BLOSUM t...
Computational Biology Amino Acids Epitopes Humans Neural Networks, Computer Receptors, Antigen, T-Cell
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