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NetMatchStar: an enhanced Cytoscape network querying app.

Fabio Rinnone1, Giovanni Micale1, Vincenzo Bonnici2

  • 1Department of Math and Computer Science, University of Catania, Catania, 95125, Italy.

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|December 2, 2015
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Summary

NetMatchStar is a Cytoscape app for finding network motifs. It identifies query graph occurrences and assesses their statistical significance using various random models.

Keywords:
approximate graph matchingbackground network modelsbiological network motifscytoscape appexact graph matchingnetwork queryingrandomizationstatistical significance

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Network Science

Background:

  • Biological networks are complex and analyzing their substructures (motifs) is crucial for understanding function.
  • Identifying recurring patterns in biological networks can reveal fundamental organizational principles.

Purpose of the Study:

  • To introduce NetMatchStar, an improved Cytoscape application for detecting network motifs.
  • To provide a tool for assessing the statistical significance of identified motifs against established random models.

Main Methods:

  • Utilizing Cytoscape for graph querying and visualization.
  • Implementing algorithms to find all occurrences of a query graph within a larger network.
  • Comparing observed motif frequencies against seven distinct randomized network models.

Main Results:

  • NetMatchStar successfully identifies all instances of a query graph in a given network.
  • The application provides a robust method for evaluating motif significance.
  • Enhanced performance and functionality compared to previous tools, including support for wildcard queries.

Conclusions:

  • NetMatchStar offers a powerful and user-friendly solution for network motif discovery and analysis in Cytoscape.
  • The tool aids researchers in identifying non-random patterns in biological networks, contributing to functional insights.