No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems
3.T.E. Turner, S. Schnell, and K. Burrage, Comput. Biol. Chem. 28, 165 (2004).
6.D.J. Wilkinson, Stochastic modelling for systems biology (Chapman & Hall/CRC, 2006).
9.G. Nicolis and I. Prigogine, Self-organization in non-equilibrium systems (Wiley-Interscience, New York, 1977).
14.N.G. van Kampen, Stochastic processes in physics and chemistry (Elsevier, Amsterdam, North-Holland, 2007).
34.D. Fange and J. Elf, PLOS Comput. Biol. 2, 637 (2006).
46.E. Hairer, S.P. Nørsett, and G. Wanner, Solving Ordinary Differential Equations I, 2nd ed. (Springer, Berlin, 2009).
50.Y. Cao and R. Erban, Bull. Math. Biology 76(12), 3051–3069 (2014).
Article metrics loading...
Stochastic modelling is critical for studying many biochemical processes in a cell, in particular when some reacting species have low population numbers. For many such cellular processes the spatial distribution of the molecular species plays a key role. The evolution of spatially heterogeneous biochemical systems with some species in low amounts is accurately described by the mesoscopic model of the Reaction-Diffusion Master Equation. The Inhomogeneous Stochastic Simulation Algorithm provides an exact strategy to numerically solve this model, but it is computationally very expensive on realistic applications. We propose a novel adaptive time-stepping scheme for the tau-leaping method for approximating the solution of the Reaction-Diffusion Master Equation. This technique combines effective strategies for variable time-stepping with path preservation to reduce the computational cost, while maintaining the desired accuracy. The numerical tests on various examples arising in applications show the improved efficiency achieved by the new adaptive method.
Full text loading...
Most read this month