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Related Experiment Video

Updated: May 7, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Using biological pathway data with paxtools.

Emek Demir1, Ozgün Babur, Igor Rodchenkov

  • 1Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.

Plos Computational Biology
|September 27, 2013
PubMed
Summary
This summary is machine-generated.

Paxtools simplifies biological pathway analysis by providing a Java library for accessing and analyzing pathway data. This open-source tool removes technical barriers, enabling scientists to focus on biological questions and precision medicine.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Biological pathway information is growing rapidly, offering potential for biological discovery and precision medicine.
  • Analyzing complex and fragmented pathway data presents significant technical challenges for researchers.

Purpose of the Study:

  • To present Paxtools, a Java library designed to simplify the access and analysis of biological pathway data.
  • To enable scientists to overcome technical barriers and focus on addressing biological questions.

Main Methods:

  • Developed Paxtools, a Java library with algorithms, components, and converters for biological pathways.
  • Ensured compatibility with the standard BioPAX language for pathway representation.
  • Made Paxtools open-source under the Lesser GNU public license (LGPL).

Main Results:

  • Paxtools facilitates the analysis of complex pathway information, aiding in identifying cellular process connections and disease-altered networks.
  • The library supports the development of predictive models for precision medicine applications.
  • Paxtools is platform-independent, requiring only a Java Runtime Environment.

Conclusions:

  • Paxtools effectively removes technical hurdles in accessing and analyzing biological pathway data.
  • The tool empowers scientists to leverage pathway information for biological discovery and translational research.
  • Open-source availability and LGPL license promote widespread adoption and integration into various software systems.