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Related Concept Videos

Cross-reactivity00:42

Cross-reactivity

Overview
B Cell Activation and Differentiation01:24

B Cell Activation and Differentiation

The adaptive immune response, a sophisticated defense mechanism, relies on the activation and differentiation of B lymphocytes, or B cells. These processes enable our bodies to mount a tailored response against specific pathogens such as bacteria, free virus particles, toxins, and parasites.
When naive B cells encounter a specific antigen that can bind to the B cell receptor (BCR) on their surface, they undergo sensitization to respond to the antigen's presence. Sensitization begins with...
Antigens Involved in Adaptive Immunity01:26

Antigens Involved in Adaptive Immunity

An antigen is any substance the immune system identifies as foreign and potentially harmful to the body, prompting an immune response. Antigens have two functional properties: immunogenicity and reactivity. Immunogenicity is the ability of an antigen to stimulate a specific immune response. At the same time, reactivity describes the antigen's ability to react with the cells and antibodies produced in response to it.
Complete Antigens
Complete antigens possess both immunogenicity and reactivity.
Diversity of Antigen Receptors01:28

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...

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Related Experiment Video

Updated: Jun 6, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

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

Published on: March 25, 2014

Recent advances in B-cell epitope prediction methods.

Yasser El-Manzalawy1, Vasant Honavar

  • 1Department of Systems and Computer Engineering, Al-Azhar University, Egypt. yasser@iastate.edu.

Immunome Research
|November 12, 2010
PubMed
Summary
This summary is machine-generated.

Identifying B-cell epitopes is crucial for vaccine design. This review covers computational methods for predicting B-cell epitopes, highlighting current limitations and future directions for improved vaccine development.

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Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
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Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

Related Experiment Videos

Last Updated: Jun 6, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

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

Published on: March 25, 2014

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

Area of Science:

  • Immunology
  • Computational Biology
  • Vaccinology

Background:

  • Accurate identification of B-cell epitopes is essential for developing effective vaccines against pathogens.
  • Experimental epitope determination is costly, time-consuming, and labor-intensive, necessitating computational approaches.
  • Existing computational tools for B-cell epitope prediction have limitations in accuracy.

Purpose of the Study:

  • To review recent advancements in computational methods for B-cell epitope prediction.
  • To identify current gaps and limitations in the state-of-the-art.
  • To propose future research directions for enhancing the reliability of these predictive methods.

Main Methods:

  • Review of recent literature on computational B-cell epitope prediction algorithms.
  • Analysis of the strengths and weaknesses of existing prediction tools.
  • Identification of emerging trends and promising methodologies in the field.

Main Results:

  • Several computational tools for B-cell epitope prediction have been developed.
  • The predictive performance of current tools is not yet optimal.
  • Gaps exist in the current methodologies, particularly in achieving high reliability.

Conclusions:

  • Computational methods are vital for accelerating B-cell epitope discovery in vaccine design.
  • Further research is needed to overcome the limitations of existing tools.
  • Improving the reliability of B-cell epitope prediction will significantly impact future vaccine development.