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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...
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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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Bacterial Gene Expression Analysis Using Microarrays
29:41

Bacterial Gene Expression Analysis Using Microarrays

Published on: May 28, 2007

Performance comparison of multiple microarray platforms for gene expression profiling.

Fang Liu1, Winston P Kuo, Tor-Kristian Jenssen

  • 1Department of Tumor Biology, Institute for Cancer Research, Norwegian Radium Hospital, Montebello, Oslo, Norway.

Methods in Molecular Biology (Clifton, N.J.)
|December 2, 2011
PubMed
Summary
This summary is machine-generated.

Comparing gene expression microarray platforms is challenging. A new framework improves cross-platform data consistency, finding exon-level probe matching superior for reliable gene expression analysis.

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09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

Area of Science:

  • Biomedical research
  • Genomics
  • Bioinformatics

Background:

  • Genome-wide gene expression microarrays are widely used in biomedical research.
  • Diverse platforms and analytical methods hinder cross-platform data comparison.
  • A standardized approach is needed for reliable analysis across different microarray technologies.

Purpose of the Study:

  • To develop a generalized framework for systematic comparisons across gene expression profiling platforms.
  • To accommodate commercial and "in-house", one-dye and two-dye platforms.
  • To enhance the consistency and comparability of gene expression data.

Main Methods:

  • Experimental design and data preprocessing protocols.
  • Cross-platform gene matching using exon-level probe sequences.
  • Measures of data consistency and biological validation (QRT-PCR).
  • Evaluation of ten diverse microarray platforms.

Main Results:

  • Exon-level probe sequence matching significantly improves cross-platform data consistency over annotation-based matching.
  • High consistency was observed for highly expressed genes; lower expression genes showed variability.
  • Commercial arrays demonstrated greater consistency than "in-house" arrays after preprocessing.
  • One-dye platforms generally showed higher consistency than two-dye platforms.

Conclusions:

  • The proposed framework provides a robust method for comparing gene expression microarray platforms.
  • Exon-level probe matching is crucial for accurate cross-platform gene expression analysis.
  • Preprocessing and platform type (commercial vs. in-house, one-dye vs. two-dye) impact data consistency.