Model systems in computational systems biology

The paper considers the question ‘what is the model?’ in a specific example of the use of computational modelling and simulation in systems biology, multi-scale models of cardiac electrophysiology. A detailed account of the construction of the computational models and simulations in these contexts shows that the modelling and simulating process is itself better understood as a hybrid and dynamic system of interacting models (in equation form), simulations and experiments, or what we have called the MSE system. That is, the MSE system is a system both as model source and with respect to the biological systems that they target. We argue that the process of constructing the MSE system as a model system is a process of constructing the grounds for comparability between the MSE system and the target domain. The ‘systems’ nature of the MSE system is foregrounded by validation experiments, which demand consideration of the whole system in order to be interpreted. We propose that validation is a process rather than a result, and that it consists in seeking maximal coherence and consistency within the MSE system, and across it and validation experimental outputs. In addition, these models invert the relationship between theory and model that holds on traditional views of models in science, according to which models are derived from theory, and seek to derive theory from models