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

16.8K
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...
16.8K
What is Gene Expression?01:42

What is Gene Expression?

132.7K
Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
132.7K
What is Gene Expression?01:36

What is Gene Expression?

10.1K
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
10.1K
What is Gene Expression?01:42

What is Gene Expression?

18.7K
18.7K

You might also read

Related Articles

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

Sort by
Same author

Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes.

Nature genetics·2026
Same author

Effects of short-term metyrapone treatment on glycaemic control in patients with mild autonomous cortisol secretion: a pilot study.

Endocrine·2026
Same author

Cortical Structure in Relation to Empathy and Psychopathy in 800 Incarcerated Men.

Biological psychiatry global open science·2026
Same author

Gene Expression at the Pluripotency Stage Predicts Pancreatic Endocrine Differentiation in iPSC Clones.

Stem cell reviews and reports·2026
Same author

Latent plasticity of the human pancreas across development, health, and disease.

bioRxiv : the preprint server for biology·2025
Same author

Erratum. Liraglutide Treatment Reverses Unconventional Cellular Defects in Induced Pluripotent Stem Cell-Derived β-Cells Harboring a Partially Functional WFS1 Variant. Diabetes 2025;74:1273-1288.

Diabetes·2025

Related Experiment Video

Updated: May 3, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.4K

Interpreting the gene expression microarray results: a user-based experience.

Erika Melissari1, Manuela Di Russo, Veronica Mariotti

  • 1Microarray Lab, Department of Surgical, Medical and Molecular Pathology and of Critical Area, University of Pisa, Pisa, Italy Email: erika.melissari@for.unipi.it, silvia.pellegrini@med.unipi.it.

Archives Italiennes De Biologie
|January 21, 2014
PubMed
Summary
This summary is machine-generated.

This study evaluates 10 gene expression analysis tools for microarray data interpretation. User-friendliness and effective outputs are crucial for biomedical researchers to fully utilize these bioinformatics tools.

More Related Videos

Bacterial Gene Expression Analysis Using Microarrays
29:41

Bacterial Gene Expression Analysis Using Microarrays

Published on: May 28, 2007

8.3K
Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

9.1K

Related Experiment Videos

Last Updated: May 3, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.4K
Bacterial Gene Expression Analysis Using Microarrays
29:41

Bacterial Gene Expression Analysis Using Microarrays

Published on: May 28, 2007

8.3K
Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

9.1K

Area of Science:

  • Bioinformatics
  • Gene Expression Analysis
  • Computational Biology

Background:

  • Numerous tools exist for interpreting gene expression microarray data.
  • Tool effectiveness relies heavily on user-friendliness for biomedical researchers.
  • Intuitive interfaces, utilities, and effective outputs are key for tool adoption.

Purpose of the Study:

  • To evaluate 10 gene expression interpretation tools for microarray data.
  • To assess tools based on usability, input/output features, and statistical capabilities.
  • To provide insights for researchers and developers regarding tool performance.

Main Methods:

  • Tested 10 gene expression analysis tools using 11 microarray datasets.
  • Evaluated tools against eight criteria: interface, usability, input submission, output representation and download, multiple gene ID submission, information sources, statistical tests, and multiple test correction methods.

Main Results:

  • Highlighted strengths and weaknesses of each evaluated tool.
  • Identified key factors influencing the practical utility of gene expression analysis software.
  • Provided a comparative analysis of tool performance in microarray data interpretation.

Conclusions:

  • User-centric design is paramount for the successful application of gene expression analysis tools.
  • This evaluation offers practical guidance for selecting and utilizing microarray interpretation software.
  • Recommendations are provided to enhance the usability and effectiveness of bioinformatics tools for researchers.