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rBiopaxParser--an R package to parse, modify and visualize BioPAX data.

Frank Kramer1, Michaela Bayerlová, Florian Klemm

  • 1Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de

Bioinformatics (Oxford, England)
|January 1, 2013
PubMed
Summary

The rBiopaxParser R package simplifies the use of Biological Pathway Exchange (BioPAX) data for bioinformatics analyses. It enables R users to efficiently parse, visualize, and modify pathway information, integrating biological knowledge into statistical methods.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Biological pathway data is crucial for bioinformatics tools.
  • Biological Pathway Exchange (BioPAX) is a standard for storing pathway information.
  • Integrating BioPAX data into statistical analyses can be challenging.

Purpose of the Study:

  • To enable R users to work with BioPAX data.
  • To facilitate the use of biological pathway knowledge in data analysis.
  • To streamline bioinformatics workflows involving pathway data.

Main Methods:

  • Development of an open-source R package, rBiopaxParser.
  • Implementation of functions for parsing BioPAX data within R.
  • Creation of tools for viewing and modifying BioPAX pathway models.

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Main Results:

  • rBiopaxParser provides functions to parse, view, and modify BioPAX data.
  • Users can access and alter specific components of BioPAX models.
  • The package supports the generation and visualization of regulatory graphs and pathways.

Conclusions:

  • rBiopaxParser enhances the utility of BioPAX data in R for bioinformatics.
  • The package integrates biological pathway knowledge into statistical analyses.
  • rBiopaxParser is available via Bioconductor for broad accessibility.