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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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PathwayAccess: CellDesigner plugins for pathway databases.

John L Van Hemert1, Julie A Dickerson

  • 1Bioinformatics and Computational Biology Department, Iowa State University, Ames, IA 50011, USA.

Bioinformatics (Oxford, England)
|July 22, 2010
PubMed
Summary
This summary is machine-generated.

PathwayAccess plugins streamline biochemical pathway modeling by connecting CellDesigner to diverse pathway databases. This enhances data integration and analysis for systems biology research.

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Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • CellDesigner offers a graphical interface for biochemical pathway description.
  • Direct export from many pathway databases to CellDesigner is often not supported.
  • This limitation hinders seamless integration and analysis of pathway data.

Purpose of the Study:

  • To develop an extensible suite of CellDesigner plugins, named PathwayAccess.
  • To enable direct connection of CellDesigner to various pathway databases.
  • To streamline the process of creating new plugins for specific databases.

Main Methods:

  • PathwayAccess plugins are implemented in Java.
  • They utilize Java application programming interfaces (APIs) to connect to databases.
  • Three specific plugins (MetNetAccess, BioCycAccess, ReactomeAccess) were developed.

Main Results:

  • PathwayAccess plugins enable direct data access from MetNetDB, BioCyc, and Reactome databases within CellDesigner.
  • Users can expose pathway data to analytical CellDesigner functions.
  • Visual integration of pathway data from multiple databases is facilitated using standard notations.

Conclusions:

  • PathwayAccess plugins significantly enhance CellDesigner's utility for systems biology.
  • They improve data accessibility, curation capabilities, and cross-database pathway integration.
  • The framework supports the creation of new plugins for broader database compatibility.