RT Journal Article
SR Electronic
T1 SBML to bond graphs: from conversion to composition
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.05.25.493355
DO 10.1101/2022.05.25.493355
A1 Shahidi, Niloofar
A1 Pan, Michael
A1 Tran, Kenneth
A1 Crampin, Edmund J
A1 Nickerson, David P
YR 2022
UL http://biorxiv.org/content/early/2022/05/29/2022.05.25.493355.abstract
AB 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 plausibile 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.HighlightsA framework to convert suitable SBML models of biochemical networks into bond graphs is developed.The framework is applied here to two interconnecting models of metabolism pathways.We automatically integrate the generated bond graph modules.We qualitatively illustrate the functionality of the composed model.Competing Interest StatementThe authors have declared no competing interest.