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In both cases, we simulated the reactions of the system using the stochastic simulation algorithm, and recorded the species numbers at a set of discrete time points, which were treated as observations of the system.
The PEMC method is integrated using the stochastic simulation algorithm, which is exact in time.
Exact analytical results for these quantities have been derived only for very simple gene regulatory systems [ 10- 12] and hence they are more commonly obtained by means of Monte Carlo simulations using the stochastic simulation algorithm (SSA) [ 13, 14].
Therefore, we performed a posterior power calculation using the stochastic simulation and estimation tool of the PsN toolkit to determine the power (95 and 99% confidence) of our study to find a clinically relevant genotype effect (at least 20%) on cyclosporine, everolimus, and tacrolimus PK.
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Specifically, we examine an important gene circuit, the bistable switch, and use the stochastic simulation algorithm to develop design principles that will enable us to produce a fast and robust switch for use in future applications.
For stochastic simulations of our system, we resort to the stochastic formulation of chemical kinetics (McQuarrie 1967), and use the stochastic simulation algorithm (SSA) due to Gillespie (1976) for our stochastic simulations of Eqs.
Observing results from a 1000 simulations using the stochastic model, the average prevalence of infection is progressively reduced with each periodic treatment as in the deterministic model.
The generate-first approach uses rules to define the total reaction network of the system which is used for the stochastic simulation.
(A – D ) The interlaced actin network used in the stochastic simulation.
Whenever possible the values of the parameters used in the stochastic simulation are the same as those in the deterministic simulations.
The solutions of these three deterministic reductions agree for a particular initial condition, which will be used for the stochastic simulation (Fig. 5 b).
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