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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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Related Experiment Video

Updated: Mar 17, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

A Microarray Tool Provides Pathway and GO Term Analysis.

Martin Koch¹, Hans-Dieter Royer^2,3, Michael Wiese⁴

¹Institute of Pharmaceutical Chemistry II, University of Bonn an der Immenburg 4, 53121 Bonn phone: 0228735210. martin.koch@uni-bonn.de.

Molecular Informatics

|July 29, 2016

Summary

This summary is machine-generated.

A new tool, maRt, simplifies gene expression profile analysis for researchers. It integrates biological data and uses parallel processing for faster, statistically significant results without needing expert bioinformatics skills.

Keywords:

Bioinformatics Genomics Medicinal chemistry

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Gene expression profile analysis requires both biological and computational expertise.
Existing tools may lack user-friendliness or integration capabilities.

Purpose of the Study:

To introduce maRt, a novel, user-friendly software for analyzing gene expression profiles.
To provide researchers with an accessible tool for obtaining statistically significant results.

Main Methods:

Development of maRt, a microarray reporting tool.
Integration of DAVID and BioMart web services for accessing gene ontology and pathway information.
Utilization of parallel processing on multi-core computers to accelerate analysis.

Main Results:

maRt generates structured HTML reports integrating diverse data sources.
The tool facilitates access to biological context for gene expression data.
Parallel processing significantly speeds up data analysis.

Conclusions:

maRt democratizes gene expression analysis, making it accessible beyond bioinformatics experts.
The software enhances biological interpretation of gene expression data.
Its RCP infrastructure supports integration of new R-based applications.