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In order to check the validity of our method, we performed simulations of the firing neurones using the Gillespie algorithm [38].
As in the companion paper and in Benayoun et al. [38], simulations of the network dynamics were carried out using the Gillespie algorithm for stochastic simulations [40].
Fig. 20 The left panel shows the pair-correlation function for resting and driven activity, for additive Gaussian noise, the right panel that for resting and driven activity, for intrinsic noise, averaged over many simulations using the Gillespie algorithm.
The system was simulated using the Gillespie algorithm [32].
All simulations were performed using the Gillespie algorithm implemented in Dizzy (http://magnet.systemsbiology.net/software/Dizzy/).net/software/Dizzy/
We have implemented this stochastic process using the Gillespie algorithm [17], which efficiently generates statistically exact realizations.
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In such a case the noise is multiplicative and intrinsic, and we used the Gillespie algorithm [38] to simulate the process.
StochPy uses the Gillespie algorithm for the stochastic simulations.
We have used the Gillespie algorithm [ 56] to introduce fluctuations in the gene expression levels.
Namely, we use the Gillespie algorithm to make a realization of the SIR epidemic model with demographic stochasticity [ 28].
Visual DSD includes a stochastic simulator that uses the Gillespie algorithm (Gillespie, 1977) to generate trajectories when the entire chemical reaction network has been pre-computed.
More suggestions(12)
using the upgma algorithm
using the lincs algorithm
using the targetscan algorithm
using the tango algorithm
using the amares algorithm
using the david algorithm
using the mcl algorithm
using the simple algorithm
using the sift algorithm
using the rma algorithm
using the sequest algorithm
using the sam algorithm
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