Chemical organisation theory is a framework developed to simplify the analysis of long-term behaviour of chemical systems. An organisation is a set of objects which are closed and self-maintaining. In this paper, we build on these ideas to develop novel techniques for formal quantitative analysis of chemical reaction networks, using discrete stochastic models represented as continuous-time Markov chains. We propose methods to identify organisations, to study quantitative properties regarding movement between these organisations and to construct an organisation-based coarse graining of the model that can be used to approximate and predict the behaviour of the original reaction network.
|Title of host publication
|14th International Conference on Computational Methods in Systems Biology (CMSB)
|Ezio Bartocci, Pietro Liò, Nicola Paoletti
|Number of pages
|Published - 2016
|Lecture Notes in Computer Science