Abstract
In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks (GRNs) in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas’ discrete parameters derives from this logical formalism. We offer a compositional approach which comes with a natural translation to the Stochastic π-Calculus. The method we propose consists in successive refinements of generalised dynamics of GRNs. We illustrate the merits and scalability of our framework on the control of the differentiation in a GRN generalising metazoan segmentation processes, and on the analysis of stable states within a large GRN studied in the scope of breast cancer researches.
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Paulevé, L., Magnin, M., Roux, O. (2011). Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus Framework. In: Priami, C., Back, RJ., Petre, I., de Vink, E. (eds) Transactions on Computational Systems Biology XIII. Lecture Notes in Computer Science(), vol 6575. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19748-2_8
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DOI: https://doi.org/10.1007/978-3-642-19748-2_8
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