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SBML to bond graphs: From conversion to composition.
Shahidi, Niloofar; Pan, Michael; Tran, Kenneth; Crampin, Edmund J; Nickerson, David P.
Affiliation
  • Shahidi N; Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand. Electronic address: nsha457@aucklanduni.ac.nz.
  • Pan M; Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Melbourne, 3010, Victoria, Australia; School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, 3010, Victoria, Australia.
  • Tran K; Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand.
  • Crampin EJ; Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Melbourne, 3010, Victoria, Australia; School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, 3010, Victoria, Australia; ARC Cent
  • Nickerson DP; Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand.
Math Biosci ; 352: 108901, 2022 10.
Article in En | MEDLINE | ID: mdl-36096376
ABSTRACT
The Systems Biology Markup Language (SBML) is a popular software-independent XML-based format for describing models of biological phenomena. The BioModels Database is the largest online repository of SBML models. Several tools and platforms are available to support the reuse and composition of SBML models. However, these tools do not explicitly assess whether models are physically plausible or thermodynamically consistent. This often leads to ill-posed models that are physically impossible, impeding the development of realistic complex models in biology. Here, we present a framework that can automatically convert SBML models into bond graphs, which imposes energy conservation laws on these models. The new bond graph models are easily mergeable, resulting in physically plausible coupled models. We illustrate this by automatically converting and coupling a model of pyruvate distribution to a model of the pentose phosphate pathway.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Programming Languages / Systems Biology Language: En Journal: Math Biosci Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Programming Languages / Systems Biology Language: En Journal: Math Biosci Year: 2022 Document type: Article