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Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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.
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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 result in visible changes...
What is Gene Expression?01:36

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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 processed and...
What is Gene Expression?01:42

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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.
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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...
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Related Experiment Video

Updated: May 14, 2026

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

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Published on: December 7, 2021

System for automatically inferring a genetic netwerk from expression profiles.

H Toh1, K Horimoto

  • 1Department of Bioinformatics, Biomolecular Engineering Research Institute, 6-2-3 Furuedai, Suita, Osaka, 565-0874 Japan.

Journal of Biological Physics
|January 25, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel system for automatically inferring genetic networks using graphical Gaussian modeling on gene expression data. The system accurately clusters gene profiles and reveals complex gene relationships for biological discovery.

Keywords:
cluster analysiscluster boundarygene expression profilegenetic networkgraphical Gaussian mmodelingmicroarray

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Gene expression profiles often exhibit similar patterns due to large datasets and limited conditions.
  • Systematic clustering of gene expression profiles is essential for inferring gene relationships.
  • Existing methods may require biological knowledge or additional analyses for clustering.

Purpose of the Study:

  • To develop an automated system for inferring genetic networks from gene expression data.
  • To introduce a novel method for automatic determination of cluster boundaries in hierarchical clustering.
  • To apply graphical Gaussian modeling to clustered profiles for network inference.

Main Methods:

  • Hierarchical clustering with automatic determination of cluster boundaries.
  • Graphical Gaussian modeling applied to clustered gene expression profiles.
  • Validation using 2467 yeast gene expression profiles.

Main Results:

  • An automated system successfully inferred a genetic network from gene expression data.
  • The system automatically determined cluster boundaries without prior biological knowledge.
  • The inferred network and clusters were analyzed for gene function and regulatory relationships.

Conclusions:

  • The developed system provides an automated approach to genetic network inference.
  • The method effectively clusters gene expression profiles and identifies relationships between genes.
  • This tool aids in understanding gene function and regulatory interactions in biological systems.