A comparative study of stochastic analysis techniques

Stochastic models are becoming increasingly popular in Systems Biology. They are compulsory, if the stochastic noise is crucial for the behavioural properties to be investigated. Thus, substantial effort has been made to develop appropriate and efficient stochastic analysis techniques. The impressive progress of hardware power and specifically the advent of multicore computers have ameliorated the computational tractability of stochastic models. We report on a comparative study focusing on the three base case techniques of stochastic analysis: exact numerical analysis, approximative numerical analysis, and simulation. For modelling we use extended stochastic Petri nets, which allows us to take advantage of structural information and to complement the stochastic analyses by qualitative analyses, belonging to the standard body of Petri net theory.

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