Abstract
In this paper we present P systems as a reliable computational modelling tool for Systems Biology that takes into account the discrete character of the quantity of components of biological systems, the inherently randomness in biological phenomena and the key role played by membranes in the functioning of living cells. We will introduce two different strategies for the evolution of P systems, namely, Multi-compartmental Gillespie’s Algorithm based on the well known Gillespie’s Algorithm but running on more than one compartment; and Deterministic Waiting Times Algorithm, an exact deterministic method. In order to illustrate these two strategies we have modelled two biological systems: the EGFR Signalling Cascade and the Quorum Sensing System in the bacterium Vibrio Fischeri. Our simulations results show that for the former system a deterministic approach is valid whereas for the latter a stochastic approach like Multi-compartmental Gillespie’s Algorithm is necessary.
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Pérez-Jiménez, M.J., Romero-Campero, F.J. (2006). P Systems, a New Computational Modelling Tool for Systems Biology. In: Priami, C., Plotkin, G. (eds) Transactions on Computational Systems Biology VI. Lecture Notes in Computer Science(), vol 4220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880646_8
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DOI: https://doi.org/10.1007/11880646_8
Publisher Name: Springer, Berlin, Heidelberg
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