ArticleComputational biology and chemistry2009
Hybrid stochastic simulations of intracellular reaction-diffusion systems.
Article in Computational biology and chemistry, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation.Computational and structural biotechnology journal · 2025Article
- Close agreement between deterministic versus stochastic modeling of first-passage time to vesicle fusion.Biophysical journal · 2022Article
- Multiscale Stochastic Reaction-Diffusion Algorithms Combining Markov Chain Models with Stochastic Partial Differential Equations.Bulletin of mathematical biology · 2019Article
- A hybrid continuous-discrete method for stochastic reaction-diffusion processes.Royal Society open science · 2016Article
- Asynchronous τ-leaping.The Journal of chemical physics · 2016Article
- Discrete-continuous reaction-diffusion model with mobile point-like sources and sinks.The European physical journal. E, Soft matter · 2016Article
- Stochastic chemical kinetics : A review of the modelling and simulation approaches.Biophysical reviews · 2013Review
- Exact and approximate stochastic simulation of intracellular calcium dynamics.Journal of biomedicine & biotechnology · 2011Review
- Multi-scale stochastic simulation of diffusion-coupled agents and its application to cell culture simulation.PloS one · 2011Article
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Abstract
With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.
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