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

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...

You might also read

Related Articles

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

Sort by
Same author

A CT-Based Radiomics Model for Evaluating Peritoneal Cancer Index in Peritoneal Metastasis Cases: A Preliminary Study.

Academic radiology·2022
Same author

Halogenated Zn<sup>2+</sup> Solvation Structure for Reversible Zn Metal Batteries.

Journal of the American Chemical Society·2022
Same author

Predicting Mismatch-Repair Status in Rectal Cancer Using Multiparametric MRI-Based Radiomics Models: A Preliminary Study.

BioMed research international·2022
Same author

Induction of tumor cell autosis by myxoma virus-infected CAR-T and TCR-T cells to overcome primary and acquired resistance.

Cancer cell·2022
Same author

FGFR1/MAPK-directed brachyury activation drives PD-L1-mediated immune evasion to promote lung cancer progression.

Cancer letters·2022
Same author

Modulating the Electronic Coordination Configuration and d-Band Center in Homo-Diatomic Fe<sub>2</sub>N<sub>6</sub> Catalysts for Enhanced Peroxymonosulfate Activation.

ACS applied materials & interfaces·2022
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 24, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Cross species analysis of microarray expression data.

Yong Lu1, Peter Huggins, Ziv Bar-Joseph

  • 1School of Computer Science and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Bioinformatics (Oxford, England)
|April 10, 2009
PubMed
Summary
This summary is machine-generated.

Cross-species microarray analysis reveals conserved gene function and dynamic responses across species. This approach offers unique biological insights beyond single-species studies, highlighting conserved gene operation.

More Related Videos

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

Related Experiment Videos

Last Updated: Jun 24, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Biological systems exhibit conserved mechanisms across species and conditions.
  • Microarrays capture dynamic, condition-specific gene expression, complementing static sequence data.
  • Integrating multi-species microarray data enables identification of genes conserved in sequence and function.

Purpose of the Study:

  • To review computational and technical challenges in cross-species microarray analysis.
  • To discuss approaches for addressing these challenges.
  • To highlight the advantages and insights gained from cross-species microarray data analysis.

Main Methods:

  • Review of existing literature on cross-species microarray data integration.
  • Discussion of computational methodologies for analyzing heterogeneous expression datasets.
  • Examination of strategies for identifying conserved gene expression patterns.

Main Results:

  • Cross-species analysis of microarray data presents significant computational and technical hurdles.
  • Developed approaches facilitate the integration and analysis of multi-species expression datasets.
  • Successful application of these methods yields insights unattainable from single-species analyses.

Conclusions:

  • Cross-species microarray analysis is a powerful tool for understanding conserved biological functions.
  • Addressing current challenges will further enhance the utility of comparative transcriptomics.
  • This approach provides a deeper understanding of gene regulation and biological system dynamics.