Some Investigations Concerning the CTMC and the ODE Model Derived From Bio-PEPA


Federica Ciocchetta, Andrea Degasperi, Jane Hillston, Muffy Calder

Proceedings of the Second Workshop From Biology to Concurrency and Back (FBTC 2008), pages 145-163
Electronic Notes in Theoretical Computer Science 229(1)
2009

Bio-PEPA is a recently defined language for the modelling and analysis of biochemical networks. It supports an abstract style of modelling, in which discrete levels of concentration within a species are considered instead of individual molecules. A finer granularity for the system corresponds to a smaller concentration step size and therefore to a greater number of concentration levels. This style of model is amenable to a variety of different analysis techniques, including numerical analysis based on a CMTC with states reflecting the levels of concentration. In this paper we present a formal definition of the CTMC with levels derived from a Bio-PEPA system. Furthermore we investigate the relationship between this CTMC and the system of ordinary differential equations (ODEs) derived from the same model. Using Kurtz's theorem, we show that the set of ODEs derived from the Bio-PEPA model is able to capture the limiting behaviour of the CTMC obtained from the same system. Finally, we define an empirical methodology to find the granularity of the Bio-PEPA system for which the ODE and the CTMC with levels are in a good agreement. The proposed definition is based on a notion of distance between the two models. We demonstrate our approach on a model of the Repressilator, a simple biochemical network with oscillating behaviour.

(keywords) Systems Biology; process algebras; analysis; ordinary differential equations; Markov chains

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Publication

— authors

Federica Ciocchetta, Andrea Degasperi, Jane Hillston, Muffy Calder

— status

published

— sort

paper in proceedings

— publication date

2009

— volume

Proceedings of the Second Workshop From Biology to Concurrency and Back (FBTC 2008)

— series

Electronic Notes in Theoretical Computer Science

— volume

229

— issue

1

— pages

145-163

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