Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

What is Gene Expression?

What is Gene Expression?

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...

What is Gene Expression?

What is Gene Expression?

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...

Chromatin Position Affects Gene Expression

Chromatin Position Affects Gene Expression

Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area.
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...

Cell Specific Gene Expression

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

mRNA Stability and Gene Expression

mRNA Stability and Gene Expression

The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
Cis-acting Elements involved in mRNA stability

Organization of Genes

Organization of Genes

You might also read

Related Articles

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

Sort by

Same author

SeOMLR: one-step multi-view latent representation with self-weighted ensemble learning for multi-omics cancer subtyping.

Bioinformatics (Oxford, England)·2026

Same author

Structure-enhanced graph meta learning for few-shot gene regulatory network inference.

Genome biology·2025

Same author

TransGRN: A Transfer Learning-Based Framework for Inferring Gene Regulatory Networks Across Cell Lines.

IEEE journal of biomedical and health informatics·2025

Same author

LGFFM: A Localized and Globalized Frequency Fusion Model for Ultrasound Image Segmentation.

IEEE transactions on medical imaging·2025

Same author

LineGRN: A Line Graph Neural Network for Gene Regulatory Network Inference.

IEEE journal of biomedical and health informatics·2025

Same author

Unveiling spatial domains from spatial multi-omics data using dual-graph regularized ensemble learning.

Communications biology·2025

Search research articles

Related Experiment Video

Updated: Feb 8, 2026

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Published on: April 14, 2010

Identifying Gene Network Rewiring by Integrating Gene Expression and Gene Network Data.

Ting Xu, Le Ou-Yang, Xiaohua Hu

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|July 12, 2018

Summary

This study introduces a novel bioinformatics method to detect changes in gene regulatory networks by combining gene expression and static network data. The approach successfully identified key genes linked to cancer subtypes and treatment responses.

More Related Videos

Author Spotlight: Advancing Gene Editing in Bamboo Leaves for Sustainable Plastic Alternatives

Author Spotlight: Advancing Gene Editing in Bamboo Leaves for Sustainable Plastic Alternatives

Published on: August 18, 2023

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

Related Experiment Videos

Last Updated: Feb 8, 2026

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Published on: April 14, 2010

Author Spotlight: Advancing Gene Editing in Bamboo Leaves for Sustainable Plastic Alternatives

Author Spotlight: Advancing Gene Editing in Bamboo Leaves for Sustainable Plastic Alternatives

Published on: August 18, 2023

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

Area of Science:

Bioinformatics
Computational Biology
Systems Biology

Background:

Inferring differential gene regulatory networks is crucial for understanding disease progression.
Existing methods primarily utilize gene expression data, overlooking valuable static gene regulatory network information.

Purpose of the Study:

To develop a novel Gaussian graphical model-based method for inferring differential networks.
To integrate both gene expression and static gene regulatory network data for improved accuracy.

Main Methods:

Developed a Gaussian graphical model approach.
Integrated gene expression data with static gene regulatory network data.
Validated the method using simulation data and The Cancer Genome Atlas (TCGA) datasets.

Main Results:

The proposed method outperforms existing state-of-the-art approaches on simulation data.
Identified significant gene network rewiring in ovarian cancers related to platinum response.
Revealed gene network differences between luminal A and basal-like breast cancer subtypes.

Conclusions:

The integrated approach effectively captures gene network rewiring across different pathological states.
Identified hub genes that are known biomarkers for platinum resistance and breast cancer intrinsic subtypes.
This method provides a powerful tool for analyzing complex biological networks in cancer research.