AIMC Topic: T-Lymphocytes
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Multi-positive contrastive learning-based cross-attention model for T cell receptor-antigen binding prediction.
Computer methods and programs in biomedicine
Aug 1, 2025
BACKGROUND AND OBJECTIVE: T cells play a vital role in the immune system by recognizing and eliminating infected or cancerous cells, thus driving adaptive immune responses. Their activation is triggered by the binding of T cell receptors (TCRs) to ep...
Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.
Ageing research reviews
Jul 1, 2025
Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent cells promotes chronic inflammation, tissue dysfunction, age-related diseases, and tumor suppression. ...
Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.
Journal of biomolecular structure & dynamics
May 1, 2025
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
Understanding TCR T cell knockout behavior using interpretable machine learning.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2025
Genetic perturbation of T cell receptor (TCR) T cells is a promising method to unlock better TCR T cell performance to create more powerful cancer immunotherapies, but understanding the changes to T cell behavior induced by genetic perturbations rema...
The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood.
Cancer research
Jun 4, 2024
UNLABELLED: T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in...
Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.
Cancer immunology research
May 2, 2024
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multipl...
A biomimetic robotic antigen-presenting system for sensitive T cell recognition.
Nature methods
May 1, 2024
TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learning.
Protein science : a publication of the Protein Society
Jan 1, 2024
The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by the major histocompatibility complex is the key to trigger the immune response. Identifying the binding rules of TCR-epitope pair is crucial for develo...
XGSEA: CROSS-species gene set enrichment analysis via domain adaptation.
Briefings in bioinformatics
Sep 2, 2021
MOTIVATION: Gene set enrichment analysis (GSEA) has been widely used to identify gene sets with statistically significant difference between cases and controls against a large gene set. GSEA needs both phenotype labels and expression of genes. Howeve...
Deep generative selection models of T and B cell receptor repertoires with soNNia.
Proceedings of the National Academy of Sciences of the United States of America
Apr 6, 2021
Subclasses of lymphocytes carry different functional roles to work together and produce an immune response and lasting immunity. Additionally to these functional roles, T and B cell lymphocytes rely on the diversity of their receptor chains to recogn...
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