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
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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:
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通讯作者:
Fadai N
Fadai N
中科院分区:
--
文献类型:
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作者:
Fadai N

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了解细胞如何在各种环境中增殖,迁移和死亡对于确定生物体如何发育和自我修复至关重要。连续统数学模型,如逻辑斯谛方程和费舍尔-柯尔莫哥洛夫方程,可以描述在常用的细胞生物学测定中观察到的全局特征,如增殖和划痕测定。然而,这些连续模型未能解释在高通量实验中观察到的单细胞水平的力学。代表单个细胞的数学建模框架,通常称为基于代理的模型,可以成功地描述这些检测的关键单细胞水平特征,但在处理包含大量细胞的群体时,计算是不可行的。在这项工作中,我们提出了一个基于代理的模型与拥挤的影响,是计算效率和匹配的logistic和Fisher-Kolmogorov方程的参数制度相关的增殖和划痕试验,分别。这种随机的基于代理的模型允许多个代理被包含在一个底层网格上的隔间内,从而减少了计算存储与现有的基于代理的模型相比。此外,我们提出了一个系统的方法,在确定一个合适的隔室大小,完全取决于测定参数。使用此隔室大小实现此基于隔室的模型可以在计算存储、代理行为的本地解析以及与模型的连续体描述的一致性之间实现平衡。
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.
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:
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DOI: --
发表时间: 2011
期刊: Physical review. E, Statistical, nonlinear, and soft matter physics
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M. Simpson;R. Baker
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发表时间: 2009
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Matthew J. Simpson
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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
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人单核白细胞趋化性:体液和细胞趋化因子的定量测定。
DOI: --
发表时间: 1972
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