Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.
| Autor: | James C Schaff, Fei Gao, Ye Li, Igor L Novak, Boris M Slepchenko |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | PLoS Computational Biology, Vol 12, Iss 12, p e1005236 (2016) |
| Druh dokumentu: | article |
| ISSN: | 1553-734X 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1005236 |
| Popis: | Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell. |
| Databáze: | Directory of Open Access Journals |
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