Function of dynamic models in systems biology: linking structure to behaviour

Christian Knüpfer, Clemens Beckstein
2013 Journal of Biomedical Semantics  
Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. Results: In this paper we describe different functional aspects of dynamic models. This description is
more » ... ally embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. Conclusion: We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process. Any progress in this area will in turn improve computer-supported modelling and simulation in Systems Biology. Bio-models are mathematical descriptions of biological processes which are used to answer biological questions. Generally, these questions are causal questions asking for mechanistic explanations of dynamic biological phenomena. In order to serve as mechanistic explanations it is necessary that the temporal behaviour of a bio-model can be simulated by means of computers. Therefore, the bio-model has to be encoded in an appropriate computerunderstandable format. System-level understanding of biological phenomena requires the integration of biomodels from different abstraction levels expressed in different modelling paradigms [4] . Computer support for modelling and simulation is an important contribution to meet the challenges in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. A first step towards such
doi:10.1186/2041-1480-4-24 pmid:24103739 pmcid:PMC3853929 fatcat:wg555nfpvra4jny6iwr5c5u4na