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Extraction and Quantification of Soluble, Radiolabeled Inositol Polyphosphates from Different Plant Species using SAX-HPLC
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LibKiSAO: a Java library for Querying KiSAO.

Anna Zhukova1, Richard Adams, Camille Laibe

  • 1EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, United Kingdom.

BMC Research Notes
|September 26, 2012
PubMed
Summary
This summary is machine-generated.

A new Java library, libKiSAO, allows easy access to the Kinetic Simulation Algorithm Ontology (KiSAO) for simulation tools. This improves algorithm selection and model re-use in Systems Biology.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • The Kinetic Simulation Algorithm Ontology (KiSAO) provides data on Systems Biology simulation algorithms, their properties, and relationships.
  • Unambiguous identification of algorithms in simulation descriptions is facilitated by KiSAO.
  • Accessing information on similar algorithms and their parameters is crucial for simulation tools.

Purpose of the Study:

  • To develop a programmatic interface for querying the KiSAO.
  • To enable simulation tools to retrieve detailed information about simulation algorithms and their characteristics.
  • To facilitate the identification of analogous algorithms for improved simulation flexibility.

Main Methods:

  • Development of libKiSAO, a Java library for interacting with the KiSAO.
  • Implementation of methods for retrieving algorithm details, parameters, and hierarchy.
  • Inclusion of functionality to search for and identify similar algorithms.

Main Results:

  • LibKiSAO provides programmatic access to KiSAO data for Java applications.
  • The library enables querying of algorithm characteristics, parameters, and relationships.
  • It supports the identification of similar algorithms for flexible simulation setup.

Conclusions:

  • LibKiSAO enhances Java application access to the OWL-encoded Kinetic Simulation Algorithm Ontology.
  • Simulation tools can leverage libKiSAO to improve the reproducibility of computational simulations.
  • The library aids in reusing models and selecting appropriate algorithms for Systems Biology simulations.