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Related Concept Videos

Enzyme-Linked Immunosorbent Assay01:33

Enzyme-Linked Immunosorbent Assay

In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen.  Enzyme-substrate reaction allows the antigen to be visualized or quantified.
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Updated: Jul 4, 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

Immune epitope database analysis resource (IEDB-AR).

Qing Zhang1, Peng Wang, Yohan Kim

  • 1Immune Epitope Database and Analysis Resource (IEDB-AR), La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.

Nucleic Acids Research
|June 3, 2008
PubMed
Summary
This summary is machine-generated.

The Immune Epitope Database Analysis Resource (IEDB-AR) has released new tools and features for predicting and analyzing B-cell and T-cell epitopes. This update enhances immunoinformatics research and epitope discovery.

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Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
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Published on: March 24, 2017

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Last Updated: Jul 4, 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
  • Bioinformatics
  • Computational Biology

Background:

  • The Immune Epitope Database Analysis Resource (IEDB-AR) is a critical platform for immunoinformatics research.
  • Accurate prediction and analysis of immune epitopes are essential for vaccine development and understanding immune responses.

Purpose of the Study:

  • To announce a new release of the IEDB-AR, introducing enhanced functionalities and novel prediction tools.
  • To expand the capabilities for epitope analysis, particularly for B-cell and T-cell epitopes.

Main Methods:

  • The IEDB-AR platform was updated with new functionalities for existing tools.
  • Eight new web-based tools were developed and integrated into the resource.
  • Specific additions include two B-cell epitope prediction tools, four T-cell epitope prediction tools, and two general analysis tools.

Main Results:

  • The updated IEDB-AR provides an expanded suite of tools for epitope prediction and analysis.
  • Users benefit from improved functionalities in existing prediction algorithms.
  • The addition of new tools broadens the scope of analyses possible within the resource.

Conclusions:

  • The latest release of IEDB-AR significantly enhances its utility for researchers in immunology and related fields.
  • These advancements facilitate more accurate and comprehensive immune epitope discovery and characterization.
  • The resource continues to be a vital hub for computational immunology research.