In the last decades, experimental investigations have evidenced the role of biological noise in cellular processes, and several stochastic approaches have been proposed to modeling and simulation of biochemical networks. Here, we review the main stochastic procedures defined for single-volume biochemical systems (SSA, tau-leaping), and discuss their practical utility and limitations. Then, within the framework of membrane systems, we propose a multi-volume generalization of the tau-leaping algorithm, called tau-DPP, feasible for the stochastic analysis of complex biochemical systems. Finally, we present a case-study application of tau-DPP to an intracellular genetic oscillator, coupled with an intercellular communication mechanism.
A Multi-volume Approach to Stochastic Modeling with Membrane Systems / D. Besozzi, P. Cazzaniga, D. Pescini, G. Mauri (NATURAL COMPUTING SERIES). - In: Algorithmic Bioprocesses / [a cura di] A. Condon, D. Harel, J.N. Kok, A. Salomaa, E. Winfree. - Berlin : Springer-Verlag, 2009. - ISBN 9783540888680. - pp. 519-542 [10.1007/978-3-540-88869-7_26]
A Multi-volume Approach to Stochastic Modeling with Membrane Systems
D. BesozziPrimo
;
2009
Abstract
In the last decades, experimental investigations have evidenced the role of biological noise in cellular processes, and several stochastic approaches have been proposed to modeling and simulation of biochemical networks. Here, we review the main stochastic procedures defined for single-volume biochemical systems (SSA, tau-leaping), and discuss their practical utility and limitations. Then, within the framework of membrane systems, we propose a multi-volume generalization of the tau-leaping algorithm, called tau-DPP, feasible for the stochastic analysis of complex biochemical systems. Finally, we present a case-study application of tau-DPP to an intracellular genetic oscillator, coupled with an intercellular communication mechanism.File | Dimensione | Formato | |
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