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• W2295877497 startingPage "20160336" @default.
• W2295877497 abstract "Numerous processes across both the physical and biological sciences are driven by diffusion. Partial differential equations are a popular tool for modelling such phenomena deterministically, but it is often necessary to use stochastic models to accurately capture the behaviour of a system, especially when the number of diffusing particles is low. The stochastic models we consider in this paper are ‘compartment-based’: the domain is discretized into compartments, and particles can jump between these compartments. Volume-excluding effects (crowding) can be incorporated by blocking movement with some probability. Recent work has established the connection between fine- and coarse-grained models incorporating volume exclusion, but only for uniform lattices. In this paper, we consider non-uniform, hybrid lattices that incorporate both fine- and coarse-grained regions, and present two different approaches to describe the interface of the regions. We test both techniques in a range of scenarios to establish their accuracy, benchmarking against fine-grained models, and show that the hybrid models developed in this paper can be significantly faster to simulate than the fine-grained models in certain situations and are at least as fast otherwise." @default.
• W2295877497 created "2016-06-24" @default.
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• W2295877497 date "2016-07-01" @default.
• W2295877497 modified "2023-09-30" @default.
• W2295877497 title "Coupling volume-excluding compartment-based models of diffusion at different scales: Voronoi and pseudo-compartment approaches" @default.
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• W2295877497 doi "https://doi.org/10.1098/rsif.2016.0336" @default.
• W2295877497 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4971222" @default.
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