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Related Concept Videos

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.
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,...

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Related Experiment Video

Updated: Jun 6, 2026

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

Enrichment map: a network-based method for gene-set enrichment visualization and interpretation.

Daniele Merico1, Ruth Isserlin, Oliver Stueker

  • 1Department of Molecular Genetics, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.

Plos One
|November 19, 2010
PubMed
Summary
This summary is machine-generated.

Enrichment Map simplifies gene list interpretation by visualizing gene-set enrichment results as a network. This method overcomes redundancy, helping researchers quickly identify key functional themes in large gene datasets.

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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
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Published on: August 16, 2017

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Published on: March 5, 2022

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Gene-set enrichment analysis (GSEA) aids in functionally characterizing large gene lists from experiments.
  • GSEA identifies statistically over-represented gene-sets (e.g., pathways) within a gene list.
  • Current GSEA software often suffers from gene-set redundancy, hindering interpretation.

Purpose of the Study:

  • To address gene-set redundancy in enrichment analysis.
  • To develop a visualization method for improved interpretation of large gene lists.
  • To facilitate the identification of major functional themes in gene expression data.

Main Methods:

  • Developed
  • Enrichment Map
  • a network-based visualization technique.
  • Represented gene-sets as nodes and gene overlap between sets as edges in a network.
  • Utilized automated network layout to cluster related gene-sets.

Main Results:

  • Enrichment Map organizes gene-sets into a network, revealing relationships and clusters.
  • The network visualization effectively reduces redundancy and simplifies the interpretation of enrichment results.
  • Users can rapidly identify major enriched functional themes within complex gene lists.

Conclusions:

  • Enrichment Map offers a significant advancement for interpreting gene-set enrichment analysis.
  • This visualization framework is applicable to any research generating gene lists.
  • Enrichment Map is a free, user-friendly plugin for the Cytoscape network visualization software.