4.6 Article

Modular assembly of dynamic models in systems biology

Journal

PLOS COMPUTATIONAL BIOLOGY
Volume 17, Issue 10, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1009513

Keywords

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Funding

  1. Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology [CE140100036]
  2. School of Mathematics and Statistics, University of Melbourne
  3. Faculty of Engineering and Information Technology, University of Melbourne

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Bond graphs combine modularity and physics-based modeling, making it an ideal framework for constructing large-scale models in systems biology. Two examples illustrate the utility of bond graphs in improving model reusability and flexibility.
It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two examples to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.

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