Bridging the scales: semantic integration of quantitative SBML in graphical multi-cellular models and simulations with EPISIM and COPASI

Abstract

MOTIVATION Biological reality can in silico only be comprehensively represented in multi-scaled models. To this end, cell behavioural models addressing the multi-cellular level have to be semantically linked with mechanistic molecular models. These requirements have to be met by flexible software workflows solving the issues of different time scales, inter-model variable referencing and flexible sub-model embedding. RESULTS We developed a novel software workflow (EPISIM) for the semantic integration of Systems Biology Markup Language (SBML)-based quantitative models in multi-scaled tissue models and simulations. This workflow allows to import and access SBML-based models. SBML model species, reactions and parameters are semantically integrated in cell behavioural models (CBM) represented by graphical process diagrams. By this, cellular states like proliferation and differentiation can be flexibly linked to gene-regulatory or biochemical reaction networks. For a multi-scale agent-based tissue simulation executable code is automatically generated where different time scales of imported SBML models and CBM have been mapped. We demonstrate the capabilities of the novel software workflow by integrating Tyson's cell cycle model in our model of human epidermal tissue homeostasis. Finally, we show the semantic interplay of the different biological scales during tissue simulation. AVAILABILITY The EPISIM platform is available as binary executables for Windows, Linux and Mac OS X at http://www.tiga.uni-hd.de. Supplementary data are available at http://www.tiga.uni-hd.de/supplements/SemSBMLIntegration.html. CONTACT niels.grabe@bioquant.uni-heidelberg.de.

DOI: 10.1093/bioinformatics/bts659

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@article{Stterlin2013BridgingTS, title={Bridging the scales: semantic integration of quantitative SBML in graphical multi-cellular models and simulations with EPISIM and COPASI}, author={Thomas S{\"{u}tterlin and Christoph Kolb and Hartmut Dickhaus and Dirk J{\"a}ger and Niels Grabe}, journal={Bioinformatics}, year={2013}, volume={29 2}, pages={223-9} }