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 τ-DPP, feasible for the stochastic analysis of complex biochemical systems. Finally, we present a case-study application of τ-DPP to an intracellular genetic oscillator, coupled with an intercellular communication mechanism.
|Titolo:||A Multi-volume Approach to Stochastic Modeling with Membrane Systems|
|Autori interni:||BESOZZI, DANIELA (Primo)|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2009|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|