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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Updated: Jun 6, 2026

Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Published on: January 7, 2019

Analysis of high-throughput ELISA microarray data.

Amanda M White¹, Don S Daly, Richard C Zangar

¹Pacific Northwest National Laboratory, Richland, WA, USA.

Methods in Molecular Biology (Clifton, N.J.)

|November 18, 2010

Summary

This summary is machine-generated.

This study presents novel statistical algorithms and open-source software for analyzing quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. These tools address unique challenges in high-throughput ELISA microarray data processing.

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Area of Science:

Biotechnology
Bioinformatics
Analytical Chemistry

Background:

Quantitative enzyme-linked immunosorbent assay (ELISA) microarrays require specialized data analysis methods.
Existing DNA microarray analysis algorithms are often unsuitable for ELISA microarray data due to fundamental differences.

Purpose of the Study:

To review and present statistically sound algorithms for high-throughput ELISA microarray data analysis.
To introduce an integrated software suite addressing each step of ELISA microarray data processing.

Main Methods:

Development of novel statistical algorithms tailored for ELISA microarray data.
Integration of algorithms into an open-source software suite (ProMAT).

Main Results:

The developed algorithms provide a statistically robust framework for ELISA microarray analysis.
The ProMAT software suite offers comprehensive tools for high-throughput data processing.

Conclusions:

The presented algorithms and software effectively address the unique analytical needs of ELISA microarrays.
Open-source availability of ProMAT facilitates wider adoption and advancement in the field.