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Related Concept Videos

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.
Hybridoma Technology01:31

Hybridoma Technology

Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
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Commonly used fusion techniques — electroporation, polyethylene glycol...
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Cross-reactivity

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Related Experiment Video

Updated: Jun 19, 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

In silico methods for predicting T-cell epitopes: Dr Jekyll or Mr Hyde?

Uthaman Gowthaman1, Javed N Agrewala

  • 1Immunology Laboratory, Institute of Microbial Technology, Sector 39A, Chandigarh-160 036, India. gowtham@imtech.res.in

Expert Review of Proteomics
|October 9, 2009
PubMed
Summary

In silico tools predict T-cell epitopes, aiding research by reducing lab work. However, their accuracy varies, presenting challenges for researchers using these computational methods.

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Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells
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Last Updated: Jun 19, 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:MHC Tetramer-based Enrichment of Epitope-specific T cells
13:58

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells

Published on: October 22, 2012

Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Experimental identification of T-cell epitopes is labor-intensive.
  • In silico tools have advanced to predict peptide-HLA binding.
  • These computational methods are increasingly adopted by the scientific community.

Purpose of the Study:

  • To review the advancements in in silico tools for T-cell epitope identification.
  • To critically assess the successes and limitations of these computational approaches.
  • To guide researchers in the effective utilization of in silico T-cell epitope prediction.

Main Methods:

  • Review of current literature on in silico T-cell epitope prediction algorithms.
  • Analysis of the performance and consistency of various prediction tools.
  • Discussion of case studies highlighting the utility and shortcomings of these methods.

Main Results:

  • In silico tools offer a promising alternative to experimental epitope mapping.
  • Significant progress has been made in predicting peptide binding to HLA alleles.
  • Inconsistencies and limitations exist, impacting the reliability of current tools.

Conclusions:

  • In silico tools are valuable but require careful validation.
  • Understanding the pitfalls is crucial for intrepid use in research.
  • Further development is needed to enhance the accuracy and consistency of epitope prediction.