CODING BIOLOGICAL SYSTEMS IN A STOCHASTIC FRAMEWORK: The Case Study of Budding Yeast Cell Cycle

摘要

In biology, modelling is mainly grounded in mathematics, and specifically on ordinary differential equations (ODEs). Using programming languages originally thought to describe networks of computers that exchange information is a complementary and emergent approach to analyze the dynamics of biological networks. In this work, we focus on the process algebra language called BlenX and we show that it is possible to easily reuse ODE models within this framework. In particular we focus on a well characterized biological network: the cell cycle of the budding yeast. This system has been studied in great details in the deterministic framework and data about a lot of mutants are available for the chosen model. It is interesting to note that the experimental phenotypic characterization of some mutants cannot be explained by the deterministic solution of the model, so in this work we propose a translation of the model in the stochastic framework in order to be able to verify if the inconsistencies are due to the noise that is affecting the system.