Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

Cytotoxic T Cells-mediated Immune Response

Cytotoxic T Cells-mediated Immune Response

Cytotoxic T cells are a vital component of the immune system. They have the remarkable ability to identify and target antigens on infected or abnormal cells. These antigens often originate from intracellular pathogens such as viruses or abnormal proteins cancer cells produce.
Immunological surveillance is the ability of immune cells to monitor and eliminate infected cells with intracellular pathogens, neoplastically transformed cells, and cells with non-self antigens. Cytotoxic T cells and NK...

Cell-mediated Immune Responses

Cell-mediated Immune Responses

T Cell Types and Functions

T Cell Types and Functions

When T cells with CD4 markers are activated, they give rise to two types of effector cells: helper T cells and regulatory T cells. Meanwhile, T cells with CD8 markers differentiate into effector cytotoxic T cells. The differentiation of CD4 T cells into helper T cell subsets, such as Th1, Th2, and Th17 cells, is dependent on the antigen type, antigen-presenting cell, and regulatory cytokines.
Th1 cells stimulate dendritic cells to express necessary co-stimulatory molecules on their surfaces for...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

FBApro: A fast, simple linear transformation for diverse metabolic modeling tasks.

ArXiv·2026

Same author

Targeting Oncomucin-driven Immunosuppression Improves the Efficacy of K-ras<sup>G12D</sup> Inhibition in Pancreatic Cancer.

Gastroenterology·2026

Same author

Fast, accurate construction of multiple sequence alignments from protein language embeddings.

bioRxiv : the preprint server for biology·2026

Same author

Single-cell transcriptomics reveals FXR1 as an actionable target for siRNA therapy in ovarian cancer.

Nature communications·2026

Same author

Preface.

Journal of computational biology : a journal of computational molecular cell biology·2026

Same author

Macrovascular tumor infiltration and circulating tumor cell cluster dynamics in patients with cancer approaching the end of life.

Nature medicine·2025

Search research articles

Related Experiment Video

Updated: Jun 26, 2025

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

Published on: June 19, 2018

Computational Methods for Predicting Key Interactions in T Cell-Mediated Adaptive Immunity.

Ryan Ehrlich¹, Eric Glynn², Mona Singh^3,2

¹School of Interdisciplinary Informatics, University of Nebraska, Omaha, Nebraska, USA;

Annual Review of Biomedical Data Science

|May 15, 2024

Summary

This summary is machine-generated.

The adaptive immune system uses T cells to fight pathogens and cancer. Computational methods predict key protein interactions for vaccine design and cancer immunotherapy, aiding researchers in understanding T cell immunity.

Keywords:

T cell receptors immunoinformatics machine learning major histocompatibility complex

More Related Videos

Measurement of T Cell Alloreactivity Using Imaging Flow Cytometry

Measurement of T Cell Alloreactivity Using Imaging Flow Cytometry

Published on: April 19, 2017

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Published on: February 6, 2017

Related Experiment Videos

Last Updated: Jun 26, 2025

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

Published on: June 19, 2018

Measurement of T Cell Alloreactivity Using Imaging Flow Cytometry

Measurement of T Cell Alloreactivity Using Imaging Flow Cytometry

Published on: April 19, 2017

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Published on: February 6, 2017

Area of Science:

Immunology
Computational Biology
Bioinformatics

Background:

The adaptive immune system provides immunological memory against pathogens and cancer.
T cells are crucial for adaptive immunity, targeting intracellular pathogens and activating B cells.
Precise antigen recognition by T cells relies on interactions between MHC proteins, peptides, and T cell receptors.

Purpose of the Study:

To provide computational researchers with an introduction to the adaptive immune system.
To review computational approaches for predicting key protein interactions in T cell-mediated immunity.
To highlight current challenges in the field.

Main Methods:

Review of computational methods for predicting protein interactions.
Analysis of major histocompatibility complex (MHC) and T cell receptor (TCR) interactions.
Focus on peptide-MHC complex formation and recognition.

Main Results:

Computational predictions are vital for applications like vaccine design and cancer immunotherapy.
Understanding T cell-antigen recognition is enhanced by computational approaches.
Several fundamental protein interactions govern T cell antigen specificity.

Conclusions:

Computational methods offer powerful tools for studying adaptive immunity.
Further development is needed to address remaining challenges in predicting T cell-mediated responses.
This work serves as a guide for computational researchers entering the field of T cell immunology.