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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...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Related Experiment Video

Updated: Jun 29, 2026

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.

Yunfeng Yang1, Mengxia Zhu, Liyou Wu

  • 1Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. yang@ornl.gov

BMC Genomics
|October 10, 2008
PubMed
Summary
This summary is machine-generated.

Data processing significantly impacts microarray reliability when using genomic DNA as a reference. Optimizing analysis techniques, including minimal replicates and logarithmic transformation, improves data quality and resolves conflicting results.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Genomic DNA as a common reference in microarray experiments has yielded conflicting reliability results.
  • This inconsistency suggests that data processing plays a crucial role in microarray data quality.

Purpose of the Study:

  • To investigate the impact of data processing on microarray reliability using genomic DNA as a reference.
  • To identify optimal data processing strategies for improving microarray data quality.

Main Methods:

  • Microarray experiments were conducted on Shewanella oneidensis.
  • Pair-wise comparisons were performed using labeled cDNA and genomic DNA as a reference.
  • Various data processing techniques were applied and assessed for inconsistency reduction.

Main Results:

  • Data quality was significantly enhanced by implementing constraints such as a minimal number of replicates.
  • Logarithmic transformation and random error analyses further improved the consistency of microarray data.
  • The study identified specific data processing steps that positively influence reliability.

Conclusions:

  • Data processing methods critically influence the quality and reliability of microarray experiments using genomic DNA as a reference.
  • These findings explain the discrepancies reported in the literature regarding this methodology.
  • The study provides a guideline for effective microarray data analysis with genomic DNA as a standard reference.