Abstract
Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.
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Abbreviations
- DAE:
-
differential algebraic equation
- PDAE:
-
partial differential algebraic equation
- PDE:
-
partial differential equation
- SBML:
-
systems biology markup language
- XML:
-
extended markup language
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Acknowledgment
This work was funded by German Ministry of Education and Research (BMBF) within the SysMAP Project (0313704).
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Wiechert, W., Noack, S., Elsheikh, A. (2009). Modeling Languages for Biochemical Network Simulation: Reaction vs Equation Based Approaches. In: Wittmann, C., Krull, R. (eds) Biosystems Engineering II. Advances in Biochemical Engineering / Biotechnology, vol 121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10_2009_64
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DOI: https://doi.org/10.1007/10_2009_64
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