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SBML Models and MathSBML

  • Bruce E. Shapiro
  • Andrew Finney
  • Michael Hucka
  • Benjamin Bornstein
  • Akira Funahashi
  • Akiya Jouraku
  • Sarah M. Keating
  • Nicolas Le Novère
  • Joanne Matthews
  • Maria J. Schilstra
Chapter

Abstract

MathSBML is an open-source, freely downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a tool-neutral, computer-readable format for representing models of biochemical reaction networks, and it is applicable to metabolic networks, cell signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, which is a standard medium for representing and transporting data that is widely supported on the Internet, as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication, and survival. In addition to Math- SBML, a number of other tools that support SBML model examination and manipulation are provided on the http://sbml.org Web site, including libSBML, which is a C/C++ library for reading SBML models; an SBML Toolbox for MATLAB; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica, as well as providing an API for model manipulation and simulation.

Key Words

SBML libSBML MathSBML systems biology XML BioModels 

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Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Bruce E. Shapiro
    • 1
  • Andrew Finney
    • 2
  • Michael Hucka
    • 3
  • Benjamin Bornstein
    • 4
  • Akira Funahashi
    • 5
  • Akiya Jouraku
    • 5
  • Sarah M. Keating
    • 6
  • Nicolas Le Novère
    • 7
  • Joanne Matthews
    • 6
  • Maria J. Schilstra
    • 6
  1. 1.Division of Biology and Biological Network Modeling CenterCalifornia Institute of TechnologyPasadenaUSA
  2. 2.Physiomics PLC OxfordOxfordUK
  3. 3.Division of Control and Dynamical Systems and Biological Network Modeling CenterCalifornia Institute of TechnologyPasadenaUSA
  4. 4.Machine Learning Systems Group, Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA
  5. 5.ERATO-SORST Kitano Symbiotic Systems ProjectJapan Science and Technology AgencyTokyoJapan
  6. 6.Science and Technology Research InstituteUniversity of HertfordshireHatfieldUK
  7. 7.Computational NeurobiologyEMBL-EBIHinxtonUK

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