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

Diversity of Antigen Receptors

Diversity of Antigen Receptors

Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...

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...

You might also read

Related Articles

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

Sort by

Same author

The Nuclear Export Signal of IκBα Drives RelB Oscillations in the Noncanonical NF-κB Pathway.

Genes to cells : devoted to molecular & cellular mechanisms·2026

Same author

Mitochondrial protein COXFA4L3 (C15ORF48) confers resistance to DNA-damaging anticancer agents by repressing mitochondrial DNA damage responses.

Scientific reports·2026

Same author

Quantification of Information Flow by Dual Reporter System and Its Application to Bacterial Chemotaxis.

Physical review letters·2026

Same author

Mixing features of transcription factors and genes enable accurate prediction of gene regulation relationships for unknown transcription factors.

NAR genomics and bioinformatics·2026

Same author

Self-organized social distancing during epidemics when the force of infection depends on susceptible and infectious behavior.

Mathematical biosciences and engineering : MBE·2026

Same author

TCR Repertoire Analysis Quantifies Effect of Irradiation on Homeostasis of iNKT Cell Development in the Thymus of Mice.

Genes to cells : devoted to molecular & cellular mechanisms·2025

Search research articles

Related Experiment Video

Updated: Sep 2, 2025

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

Published on: January 12, 2021

Machine Learning Approaches to TCR Repertoire Analysis.

Yotaro Katayama¹, Ryo Yokota², Taishin Akiyama^3,4

¹Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.

Frontiers in Immunology

|August 1, 2022

Summary

Machine learning and deep learning are revolutionizing immunological research, particularly for T cell receptor repertoire analysis. These advanced methods offer new ways to assess immune system health and detect abnormalities.

Keywords:

T cell T cell receptor deep learning immunoinformatics machine learning

More Related Videos

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

Published on: September 10, 2017

Retroviral Transduction of Bone Marrow Progenitor Cells to Generate T-cell Receptor Retrogenic Mice

Retroviral Transduction of Bone Marrow Progenitor Cells to Generate T-cell Receptor Retrogenic Mice

Published on: July 11, 2016

Related Experiment Videos

Last Updated: Sep 2, 2025

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

Published on: January 12, 2021

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

Published on: September 10, 2017

Retroviral Transduction of Bone Marrow Progenitor Cells to Generate T-cell Receptor Retrogenic Mice

Retroviral Transduction of Bone Marrow Progenitor Cells to Generate T-cell Receptor Retrogenic Mice

Published on: July 11, 2016

Area of Science:

Immunological research
Bioinformatics
Computational biology

Background:

Genome sequencing advancements have led to a surge in immunological data volume and complexity.
Data and database platforms are crucial for advancing machine learning applications in immunology.

Purpose of the Study:

To review recent machine learning and deep learning methods for T cell receptor repertoire analysis.
To discuss the future prospects of these computational approaches in immunology.

Main Methods:

Review of machine learning algorithms applied to immunological datasets.
Analysis of deep learning techniques for T cell receptor repertoire analysis.
Exploration of data and database platforms facilitating these analyses.

Main Results:

Identification of key machine learning and deep learning methodologies in repertoire analysis.
Highlighting the growing importance of computational approaches in understanding immune system states.
Demonstrating the potential of these methods in detecting immune abnormalities.

Conclusions:

Machine learning and deep learning are pivotal for analyzing T cell receptor repertoires.
These technologies are essential for advancing the assessment of immune system status and disease.
Future research should focus on further developing and applying these advanced analytical techniques.