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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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STON: exploring biological pathways using the SBGN standard and graph databases.

Vasundra Touré1,2, Alexander Mazein3, Dagmar Waltemath4

  • 1Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany. vasundra.toure@uni-rostock.de.

BMC Bioinformatics
|December 7, 2016
PubMed
Summary
This summary is machine-generated.

STON is a Java framework that translates biological pathways into a graph database format. This enables efficient querying and analysis of complex biological networks for systems biology and medicine.

Keywords:
Graph databaseNeo4jSystems biologySystems biology graphical notationSystems medicine

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Area of Science:

  • Systems Biology
  • Systems Medicine
  • Bioinformatics

Background:

  • Biological data is extensive, complex, and heterogeneous.
  • Graphs naturally represent biological networks.
  • Graph databases offer efficient storage and querying of biological relationships.

Purpose of the Study:

  • To present STON (SBGN TO Neo4j), a Java-based framework.
  • To import and translate biological pathways into a Neo4j graph database format.

Main Methods:

  • Utilizing the Systems Biology Graphical Notation (SBGN).
  • Developing a Java framework for data translation.
  • Employing the Neo4j graph database for storage and querying.

Main Results:

  • STON successfully imports and translates metabolic, signaling, and gene regulatory pathways.
  • Biological pathways are represented in a graph-oriented format compatible with Neo4j.

Conclusions:

  • STON leverages graph databases for efficient storage and querying of complex biological pathways.
  • Facilitates subnetwork identification, cross-level network linking, and common pattern discovery.