Accurate and efficient discretisations for stochastic models providing near agent-based spatial resolution at low computational cost
Accurate and efficient discretisations for stochastic models providing near agent-based spatial resolution at low computational cost
复制标题
准确高效的随机模型离散化以低计算成本提供近乎基于代理的空间分辨率
DOI:
10.1101/686030
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Fadai N
中科院分区:
文献类型:
--
作者:
Fadai N
Understanding how cells proliferate, migrate, and die in various environments is essential in determining how organisms develop and repair themselves. Continuum mathematical models, such as the logistic equation and the Fisher-Kolmogorov equation, can describe the global characteristics observed in commonly-used cell biology assays, such as proliferation and scratch assays. However, these continuum models fail to account for single-cell-level mechanics observed in high-throughput experiments. Mathematical modelling frameworks that represent individual cells, often called agent-based models, can successfully describe key single-cell-level features of these assays, but are computationally infeasible when dealing with populations containing large numbers of cells. In this work, we propose an agent-based model with crowding effects that is computationally efficient and matches the logistic and Fisher-Kolmogorov equations in parameter regimes relevant to proliferation and scratch assays, respectively. This stochastic agent-based model allows multiple agents to be contained within compartments on an underlying lattice, thereby reducing the computational storage compared to existing agent-based models. Additionally, we propose a systematic method in determining a suitable compartment size that depends exclusively on assay parameters. Implementing this compartment-based model with this compartment size provides a balance between computational storage, local resolution of agent behaviour, and agreement with the continuum description of the model.
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DOI:
10.1093/jnci/53.3.661
发表时间:
1974-01-01
期刊:
JOURNAL OF THE NATIONAL CANCER INSTITUTE
影响因子:
--
作者:
CAILLEAU, R;YOUNG, R;REEVES, WJ
通讯作者:
REEVES, WJ
DOI:
--
发表时间:
2011
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
M. Simpson;R. Baker
通讯作者:
R. Baker
DOI:
--
发表时间:
2009
期刊:
影响因子:
--
作者:
Matthew J. Simpson
通讯作者:
Matthew J. Simpson
DOI:
--
发表时间:
2009
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
M. Simpson;K. Landman;B. Hughes
通讯作者:
B. Hughes
影响因子:
4.4
作者:
R. Snyderman;Leonard C. Altman;Marvin S. Hausman;S. E. Mergenhagen
通讯作者:
S. E. Mergenhagen