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

Protein Networks02:26

Protein Networks

3.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.6K
Protein Networks02:26

Protein Networks

1.8K
1.8K
Gene-Environment Interactions01:20

Gene-Environment Interactions

1.4K
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
1.4K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
Genetic Screens02:46

Genetic Screens

4.6K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.6K
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K

You might also read

Related Articles

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

Sort by
Same author

Data of transcriptional effects of the merbarone-mediated inhibition of TOP2.

Data in brief·2022
Same author

Distribution level electric current consumption and meteorological data set of the east region of Paraguay.

Data in brief·2022
Same author

Genome-wide prediction of topoisomerase IIβ binding by architectural factors and chromatin accessibility.

PLoS computational biology·2021
Same author

Computational Methods for the Analysis of Genomic Data and Biological Processes.

Genes·2020
Same author

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

Genes·2020
Same author

Computational Analysis of the Global Effects of <i>Ly6E</i> in the Immune Response to Coronavirus Infection Using Gene Networks.

Genes·2020

Related Experiment Video

Updated: Apr 22, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K

Gene network biological validity based on gene-gene interaction relevance.

Francisco Gómez-Vela1, Norberto Díaz-Díaz1

  • 1School of Engineering, Pablo de Olavide University, 41013 Seville, Spain.

Thescientificworldjournal
|October 9, 2014
PubMed
Summary

GeneNetVal validates gene networks using KEGG metabolic pathways. This method assesses gene-gene interaction relevance, improving the reliability of gene network inference algorithms.

More Related Videos

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

16.6K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

1.7K

Related Experiment Videos

Last Updated: Apr 22, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K
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

16.6K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

1.7K

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Gene networks are essential for modeling biological processes and extracting knowledge from gene expression data.
  • Validating inferred gene relationships is critical for ensuring the precision of gene network inference algorithms.
  • KEGG metabolic pathways are a widely used resource for biological knowledge and gene relationship analysis.

Purpose of the Study:

  • To introduce GeneNetVal, a novel methodology for assessing the biological validity of inferred gene networks.
  • To leverage KEGG metabolic pathways for evaluating the relevance of gene-gene interactions.
  • To provide a robust validation framework for gene network inference.

Main Methods:

  • Developed GeneNetVal, a methodology for gene network validation.
  • Converted KEGG pathways into a gene association network.
  • Proposed a novel matching distance metric based on gene-gene interaction relevance.

Main Results:

  • GeneNetVal's performance was evaluated through ROC analysis, demonstrating its effectiveness.
  • A randomness study showed GeneNetVal's robustness against increased noise in input networks.
  • The methodology successfully demonstrated its ability to detect the biological functionality of gene networks.

Conclusions:

  • GeneNetVal offers a reliable approach to validate gene networks using KEGG metabolic pathway data.
  • The proposed method enhances the trustworthiness of gene network inference by assessing biological relevance.
  • GeneNetVal contributes to more accurate biological process modeling and knowledge extraction from gene expression data.