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Related Experiment Video

Updated: Dec 28, 2025

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

T Cell Epitope Predictions.

Bjoern Peters^1,2, Morten Nielsen^3,4, Alessandro Sette^1,2

¹Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, California 92037, USA; email: bpeters@lji.org, alex@lji.org.

Annual Review of Immunology

|February 12, 2020

Summary

This summary is machine-generated.

T cells recognize specific T cell epitopes presented by MHC molecules, crucial for immune responses. Computational methods predict these epitopes, aiding research in various diseases and guiding experimental studies.

Keywords:

T cells benchmarking databases immune epitopes machine learning

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Published on: March 8, 2012

Area of Science:

Immunology
Computational Biology

Background:

T cells survey the body by monitoring Major Histocompatibility Complex (MHC)-bound ligands on cell surfaces.
T cell epitopes are specific MHC ligands that elicit a T cell immune response, vital for understanding immunity.

Purpose of the Study:

To highlight the importance of identifying T cell epitopes for tracking and stimulating T cells in various immune-related conditions.
To introduce computational approaches for predicting T cell epitopes due to the complexity of epitope mapping.

Main Methods:

Review of T cell epitope recognition mechanisms.
Discussion of computational methods for predicting T cell epitopes.

Main Results:

T cell epitope recognition is influenced by an individual's genetic makeup (MHC molecules) and environmental exposures.
Computational prediction of T cell epitopes is essential for guiding experimental epitope mapping.

Conclusions:

Accurate T cell epitope identification is critical for advancing research in infectious diseases, allergies, autoimmunity, transplantation, and cancer.
Computational epitope prediction tools enhance the analysis of immunogenic potential and experimental study design.