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Related Concept Videos

DNA Microarrays02:34

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...
Real Time RT-PCR02:57

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Updated: Jun 4, 2026

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

Calculation of absolute expression values for DNA microarray data.

Kazuro Shimokawa, Rimantas Kodzius, Yonehiro Matsumura

    CSH Protocols
    |March 2, 2011
    PubMed
    Summary
    This summary is machine-generated.

    DNA microarrays offer cost-effective gene expression analysis but often lack absolute values. This study introduces a method using external data like expressed sequence tags (ESTs) and CAGE tags to convert microarray data into absolute expression levels.

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    Area of Science:

    • Molecular Biology
    • Genomics
    • Bioinformatics

    Background:

    • DNA microarrays provide cost-effective, comprehensive gene expression data.
    • Microarray data often lacks accuracy and provides relative, not absolute, expression values.
    • Existing methods struggle to quantify absolute mRNA levels, limiting experimental precision.

    Purpose of the Study:

    • To develop a novel method for converting DNA microarray data into absolute expression values.
    • To enhance the reliability and interpretability of gene expression measurements.
    • To address the experimental deficiency of relative expression data.

    Main Methods:

    • Utilizing external data sources, including expressed sequence tags (ESTs) and cap analysis of gene expression (CAGE) tags.
    • Developing a computational procedure to integrate external data with microarray output.
    • Establishing a workflow for transforming relative microarray signals into absolute transcript quantities.

    Main Results:

    • Successfully converted relative microarray expression data to absolute values.
    • Demonstrated the feasibility of using ESTs and CAGE tags for absolute quantification.
    • Provided a more accurate representation of mRNA molecule numbers per sample.

    Conclusions:

    • The new method significantly improves the accuracy of DNA microarray data.
    • This approach enables the determination of absolute gene expression levels, enhancing biological interpretation.
    • The integration of external data provides a robust solution for quantitative gene expression analysis.