AIMC Topic: Receptors, Antigen, T-Cell

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Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Science (New York, N.Y.) Feb 21, 2025
Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system's own record of antigen exposures encoded by receptors on B cells and T ce...
COVID-19 SARS-CoV-2 HIV Infections Humans Machine Learning B-Lymphocytes Autoimmune Diseases Influenza, Human Receptors, Antigen, T-Cell Diabetes Mellitus, Type 1 Lupus Erythematosus, Systemic Infections Receptors, Antigen, B-Cell
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Deep learning-based prediction of autoimmune diseases.

Scientific reports Feb 7, 2025
Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking body tissues. Their etiology involves multiple factors such as genetics, environmental factors, and abnormalities in immune cells, making prediction ...
Neural Networks, Computer ROC Curve Humans T-Lymphocytes Receptors, Antigen, T-Cell Autoimmune Diseases Deep Learning Diabetes Mellitus, Type 1 Multiple Sclerosis
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Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma.

Apoptosis : an international journal on programmed cell death Feb 4, 2025
The T Cell Receptor (TCR) significantly contributes to tumor immunity, whereas the intricate interplay with the Hepatocellular Carcinoma (HCC) microenvironment and clinical significance remains largely unexplored. Here, we aimed to examine the functi...
Tumor Microenvironment Humans Male Receptors, Antigen, T-Cell Cell Line, Tumor Middle Aged Machine Learning Gene Expression Regulation, Neoplastic Liver Neoplasms Prognosis Carcinoma, Hepatocellular Signal Transduction Female
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Feature selection enhances peptide binding predictions for TCR-specific interactions.

Frontiers in immunology Jan 23, 2025
INTRODUCTION: T-cell receptors (TCRs) play a critical role in the immune response by recognizing specific ligand peptides presented by major histocompatibility complex (MHC) molecules. Accurate prediction of peptide binding to TCRs is essential for a...
Mice Peptides Machine Learning Peptide Library Receptors, Antigen, T-Cell Animals Protein Binding
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Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Journal of chemical information and modeling Jan 7, 2025
Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a ...
Protein Interaction Mapping Machine Learning Receptors, Antigen, T-Cell Protein Binding Proteins
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Exploring the potential of structure-based deep learning approaches for T cell receptor design.

PLoS computational biology Sep 30, 2024
Deep learning methods, trained on the increasing set of available protein 3D structures and sequences, have substantially impacted the protein modeling and design field. These advancements have facilitated the creation of novel proteins, or the optim...
Protein Conformation Protein Engineering Protein Binding Computational Biology Models, Molecular Humans Deep Learning Receptors, Antigen, T-Cell
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TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets.

Frontiers in immunology Aug 16, 2024
Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-epitope specificity achieve high performance metrics on test datasets which include sequences that are also part of the training set but fail to gener...
Protein Binding Humans Machine Learning Computational Biology Epitopes, T-Lymphocyte Support Vector Machine Receptors, Antigen, T-Cell
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Cancer Immunotherapies Ignited by a Thorough Machine Learning-Based Selection of Neoantigens.

Advanced biology Jul 6, 2024
Identification of neoantigens, derived from somatic DNA alterations, emerges as a promising strategy for cancer immunotherapies. However, not all somatic mutations result in immunogenicity, hence, efficient tools to predict the immunogenicity of neoe...
Machine Learning Neoplasms Receptors, Antigen, T-Cell Immunotherapy Antigens, Neoplasm Humans HLA Antigens
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A real-world pharmacovigilance study on cardiovascular adverse events of tisagenlecleucel using machine learning approach.

Scientific reports Jun 13, 2024
Chimeric antigen receptor T-cell (CAR-T) therapies are a paradigm-shifting therapeutic in patients with hematological malignancies. However, some concerns remain that they may cause serious cardiovascular adverse events (AEs), for which data are scar...
Immunotherapy, Adoptive Child Receptors, Antigen, T-Cell Pharmacovigilance Humans Middle Aged Hematologic Neoplasms Machine Learning Adolescent Aged Male Female Child, Preschool Cardiovascular Diseases Young Adult Adult
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Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing.

British journal of cancer Jun 7, 2024
BACKGROUND: It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for ident...
Humans Machine Learning Tumor Microenvironment Transcriptome Single-Cell Analysis CD8-Positive T-Lymphocytes Receptors, Antigen, T-Cell Gastrointestinal Neoplasms Antigens, Neoplasm Lymphocytes, Tumor-Infiltrating
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