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Cross-reactivity

Cross-reactivity

Enzyme-Linked Immunosorbent Assay

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: May 22, 2026

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

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

Published on: March 25, 2014

Immune epitope database analysis resource.

Yohan Kim¹, Julia Ponomarenko, Zhanyang Zhu

¹La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA 92037, USA.

Nucleic Acids Research

|May 22, 2012

Summary

This summary is machine-generated.

The Immune Epitope Database Analysis Resource (IEDB-AR) now offers advanced tools for predicting T- and B-cell epitopes. These updated epitope prediction tools show improved performance and expanded access options for researchers.

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Last Updated: May 22, 2026

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

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Published on: March 25, 2014

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

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

Published on: March 24, 2017

Area of Science:

Immunoinformatics
Computational Biology
Bioinformatics

Background:

The Immune Epitope Database Analysis Resource (IEDB-AR) provides tools for analyzing immune responses.
Previous versions focused on T-cell epitope prediction and B-cell targets.

Purpose of the Study:

To introduce significant updates and new tools within the IEDB-AR.
To enhance the prediction accuracy and accessibility of epitope analysis tools.

Main Methods:

Integration of a new generation of peptide:MHC binding and T-cell epitope predictive algorithms.
Development of a novel B-cell epitope prediction tool.
Updating homology mapping for discontinuous epitopes on 3D structures.
Expanding programmatic access via web interface and downloadable software packages.

Main Results:

Demonstrated considerable improvement in predictive performance for peptide:MHC-I binding, validated by external studies and competitions.
Successfully added a new B-cell epitope prediction tool.
Enhanced homology mapping capabilities for complex epitope structures.
Increased accessibility through diverse access methods, including programmatic and downloadable options.

Conclusions:

The updated IEDB-AR offers significantly enhanced capabilities for epitope prediction and analysis.
Expanded accessibility broadens the resource's utility for a wider research community.
These advancements facilitate more accurate and comprehensive studies of immune responses.