AIMC Topic: Major Histocompatibility Complex

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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...
Humans Machine Learning Algorithms T-Lymphocytes Peptides Receptors, Antigen, T-Cell Protein Binding Computational Biology Major Histocompatibility Complex
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RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Bioinformatics (Oxford, England) Jan 2, 2024
MOTIVATION: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the developmen...
Peptides Deep Learning Protein Binding Histocompatibility Antigens Class I Major Histocompatibility Complex
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New tools for MHC research from machine learning and predictive algorithms to the tumour immunopeptidome.

Immunology Jul 1, 2018
At a time when immunology seeks to progress ever more rapidly from characterization of a microbial or tumour antigen to the immune correlates that may define protective T-cell immunity, there is a need for robust tools to enable accurate predictions ...
Humans Machine Learning Research T-Lymphocytes Neoplasms Epitopes, T-Lymphocyte Peptides Cancer Vaccines Immunotherapy, Adoptive Major Histocompatibility Complex
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