Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

21.9K
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...
21.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.

Genetic epidemiologyĀ·2026
Same author

Heterozygous Nonsense Mutation in the Nuclear Transport Factor <i>KPNA7</i>, a Maternal Factor Active in Embryonic Tissues, Causes Autosomal Dominant Otosclerosis.

International journal of molecular sciencesĀ·2026
Same author

Safety of intravascular administration of umbilical-cord-derived mesenchymal stromal cells: an updated systematic review and meta-analysis.

Stem cells translational medicineĀ·2026
Same author

A precision approach to translational research in acute lung injury.

American journal of respiratory and critical care medicineĀ·2026
Same author

Systemic and Local Adiposity in the Bone Marrow Microenvironment Associated With Improved Prognosis in Hodgkin Lymphoma: Imaging and Molecular Analysis.

International journal of cancerĀ·2026
Same author

The PPARĪ²/Delta-Induced Mesenchymal Stromal Cell Secretome Has Cytoprotective Effects via ANGPTL4 in a Pre-Clinical Model of Acute Lung Inflammation.

FASEB journal : official publication of the Federation of American Societies for Experimental BiologyĀ·2026
Same journal

Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB.

Microarrays (Basel, Switzerland)Ā·2017
Same journal

Microarray Selection of Cooperative Peptides for Modulating Enzyme Activities.

Microarrays (Basel, Switzerland)Ā·2017
Same journal

Avian and Mammalian Facilitative Glucose Transporters.

Microarrays (Basel, Switzerland)Ā·2017
Same journal

Use of a Pan-Genomic DNA Microarray in Determination of the Phylogenetic Relatedness among Cronobacter spp. and Its Use as a Data Mining Tool to Understand Cronobacter Biology.

Microarrays (Basel, Switzerland)Ā·2017
Same journal

A New Distribution Family for Microarray Data.

Microarrays (Basel, Switzerland)Ā·2017
Same journal

DNAĀ Microarray-BasedĀ ScreeningĀ andĀ  CharacterizationĀ ofĀ TraditionalĀ ChineseĀ Medicine.

Microarrays (Basel, Switzerland)Ā·2017
See all related articles

Related Experiment Video

Updated: Mar 15, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

4.9K

Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery.

Christopher J Walsh1,2, Pingzhao Hu3, Jane Batt4,5

  • 1Keenan and Li Ka Shing Knowledge Institute of Saint Michael's Hospital, Toronto ON M5B 1W8, Canada. chrisj.walsh@mail.utoronto.ca.

Microarrays (Basel, Switzerland)
|September 8, 2016
PubMed
Summary
This summary is machine-generated.

Integrating microarray data from different platforms enhances biomarker discovery and reliability. This review offers practical guidance for researchers on cross-platform integration methods to improve gene signature robustness.

Keywords:
biomarkermeta-analysismicroarray platformnormalization

More Related Videos

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

6.1K
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

11.0K

Related Experiment Videos

Last Updated: Mar 15, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

4.9K
Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
08:20

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Published on: May 21, 2019

6.1K
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

11.0K

Area of Science:

  • Bioinformatics
  • Genomics
  • Biostatistics

Background:

  • Vast amounts of public microarray data offer diagnostic and prognostic potential.
  • Integrating data from different microarray platforms is crucial for robust biomarker discovery.
  • Cross-platform integration improves the reproducibility and robustness of gene signature biomarkers.

Purpose of the Study:

  • To provide evidence-based, practical guidance for researchers on cross-platform microarray data integration.
  • To highlight the importance of understanding comparative performance and pitfalls of integration methods.
  • To facilitate biomarker discovery through effective data integration.

Main Methods:

  • Review of statistical methods and software for microarray platform integration.
  • Categorization of integration approaches into early-stage (normalization) and late-stage (meta-analysis).
  • Evidence-based assessment of comparative performance and potential pitfalls.

Main Results:

  • Cross-platform integration, when properly executed, enhances biomarker reproducibility and robustness.
  • A variety of statistical methods and software tools are available for platform integration.
  • Understanding method-specific performance is critical for successful implementation.

Conclusions:

  • Effective cross-platform integration is key to unlocking the full potential of public microarray data for biomarker discovery.
  • Researchers need practical guidance to navigate the complexities of different integration methods.
  • Careful selection and implementation of integration strategies are essential for reliable gene signature biomarkers.