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

Editorial: Networks and graphs in biological data: current methods, opportunities and challenges.

Frontiers in bioinformatics·2025
Same author

T cell responses and clinical symptoms among infants with congenital cytomegalovirus infection.

JCI insight·2024
Same author

Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research.

American journal of physiology. Heart and circulatory physiology·2024
Same author

Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data.

SN computer science·2023
Same author

The Importance of Weakly Co-Evolving Residue Networks in Proteins is Revealed by Visual Analytics.

Frontiers in bioinformatics·2022
Same author

Chromatin structure in cancer.

BMC molecular and cell biology·2022
Same journal

Mammalian Respiratory Chain Complex Assemblies and Their Links to Mitochondria Stress-Induced Human Diseases.

Advances in experimental medicine and biology·2026
Same journal

Enzyme Assemblies in Nucleotide Metabolism: Structure, Regulation, and Disease Implications.

Advances in experimental medicine and biology·2026
Same journal

The Pyruvate Dehydrogenase Complex: A 90-Year-Old Enigma Shaping the Future of Structural Enzymology.

Advances in experimental medicine and biology·2026
Same journal

Regulation of the Anti-termination RNA Transcription Complex by Lon-Mediated Lambda N Degradation.

Advances in experimental medicine and biology·2026
Same journal

PCNA Macromolecular Complexes: PCNA Serves as a Molecular Hub Regulating Multiple Cellular Processes Inside and Outside of the Nucleus.

Advances in experimental medicine and biology·2026
Same journal

Dynamic Assemblies in Genome Maintenance.

Advances in experimental medicine and biology·2026
See all related articles

Related Experiment Video

Updated: Jun 3, 2026

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs
07:27

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs

Published on: August 3, 2011

Dramatically reduced precision in microarray analysis retains quantitative properties and provides additional

William C Ray1

  • 1The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, OH 43205, USA. ray.29@osu.edu

Advances in Experimental Medicine and Biology
|March 25, 2011
PubMed
Summary
This summary is machine-generated.

Microarray analysis can now be hypothesis-driven using simplified gene expression profiles. Reduced data retains key biological insights, enabling precise pattern searching and verbal descriptions for gene expression analysis.

More Related Videos

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays
10:58

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Published on: December 3, 2010

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
16:24

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

Published on: February 21, 2014

Related Experiment Videos

Last Updated: Jun 3, 2026

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs
07:27

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs

Published on: August 3, 2011

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays
10:58

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Published on: December 3, 2010

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
16:24

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

Published on: February 21, 2014

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Microarray technology is crucial for analyzing nucleic acid molecule differences.
  • It detects mRNA shifts from environmental changes or drug interactions.
  • Current methods lack hypothesis-directed analysis capabilities.

Purpose of the Study:

  • To develop hypothesis-directed analysis for microarray data.
  • To demonstrate that reduced descriptions capture biologically relevant expression profiles.
  • To enable pattern searching and verbal descriptions for gene expression data.

Main Methods:

  • Reducing microarray expression profiles to human-readable descriptions.
  • Applying pattern searching techniques to these reduced descriptions.
  • Comparing clustering results from reduced versus full precision data.

Main Results:

  • Biologically relevant aspects of expression profiles are captured by precision-reduced descriptions.
  • Reduced descriptions, even at single-bit precision, reproduce clustering results.
  • Verbal descriptions of expression profiles are quantitative and compatible with reduced data analysis.

Conclusions:

  • Precision-reduced descriptions enable hypothesis-directed microarray analysis.
  • Simplified gene expression data retains significant biological information.
  • This approach facilitates more targeted and interpretable gene expression studies.