Gillespie’s direct method is a stochastic simulation algorithm that may be used to calculate the steady state solution of a chemically reacting system. Recently the all possible states method was introduced as a way of accelerating the convergence of the simulations. We demonstrate that while the all possible states (APS) method does reduce the number of required trajectories, it is actually much slower than the original algorithm for most problems. We introduce the elapsed time method, which reformulates the process of recording the species populations. The resulting algorithm yields the same results as the original method, but is more efficient, particularly for large models. In implementing the elapsed time method, we present robust meth...
Recently the application of the quasi-steady-state approximation QSSA to the stochastic simulation a...
The quasi-steady-state approximation (QSSA) is a model reduction technique used to remove highly rea...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
One can generate trajectories to simulate a system of chemical reactions using either Gillespie's di...
The stochastic simulation algorithm (SSA), first proposed by Gillespie, has become the workhorse of ...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation...
International audienceStochastic approaches in systems biology are being used increasingly to model ...
This paper discusses new simulation algorithms for stochastic chemical kinetics that exploit the lin...
Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation...
AbstractStochastic approaches in systems biology are being used increasingly to model the heterogene...
There are two fundamental ways to view coupled systems of chemical equations: as continuous, repres...
Recently the application of the quasi-steady-state approximation _QSSA_ to the stochastic simulation...
In this paper we examine the different formulations of Gillespie's stochastic simulation algorithm (...
One of the most versatile modeling formalism is the one given by Markov chains as used for the perfo...
Recently the application of the quasi-steady-state approximation QSSA to the stochastic simulation a...
The quasi-steady-state approximation (QSSA) is a model reduction technique used to remove highly rea...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
One can generate trajectories to simulate a system of chemical reactions using either Gillespie's di...
The stochastic simulation algorithm (SSA), first proposed by Gillespie, has become the workhorse of ...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation...
International audienceStochastic approaches in systems biology are being used increasingly to model ...
This paper discusses new simulation algorithms for stochastic chemical kinetics that exploit the lin...
Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation...
AbstractStochastic approaches in systems biology are being used increasingly to model the heterogene...
There are two fundamental ways to view coupled systems of chemical equations: as continuous, repres...
Recently the application of the quasi-steady-state approximation _QSSA_ to the stochastic simulation...
In this paper we examine the different formulations of Gillespie's stochastic simulation algorithm (...
One of the most versatile modeling formalism is the one given by Markov chains as used for the perfo...
Recently the application of the quasi-steady-state approximation QSSA to the stochastic simulation a...
The quasi-steady-state approximation (QSSA) is a model reduction technique used to remove highly rea...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...