Erban Radek, Winkelmann Stefanie
Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.
Zuse Institute Berlin (ZIB), Takustrasse 7, 14195, Berlin, Germany.
Bull Math Biol. 2024 Nov 27;87(1):6. doi: 10.1007/s11538-024-01377-y.
The multi-grid reaction-diffusion master equation (mgRDME) provides a generalization of stochastic compartment-based reaction-diffusion modelling described by the standard reaction-diffusion master equation (RDME). By enabling different resolutions on lattices for biochemical species with different diffusion constants, the mgRDME approach improves both accuracy and efficiency of compartment-based reaction-diffusion simulations. The mgRDME framework is examined through its application to morphogen gradient formation in stochastic reaction-diffusion scenarios, using both an analytically tractable first-order reaction network and a model with a second-order reaction. The results obtained by the mgRDME modelling are compared with the standard RDME model and with the (more detailed) particle-based Brownian dynamics simulations. The dependence of error and numerical cost on the compartment sizes is defined and investigated through a multi-objective optimization problem.
多网格反应扩散主方程(mgRDME)是对标准反应扩散主方程(RDME)所描述的基于随机隔室的反应扩散建模的一种推广。通过为具有不同扩散常数的生化物种在晶格上启用不同的分辨率,mgRDME方法提高了基于隔室的反应扩散模拟的准确性和效率。通过将mgRDME框架应用于随机反应扩散场景中的形态发生素梯度形成来进行研究,使用了一个解析上易于处理的一级反应网络和一个具有二级反应的模型。将mgRDME建模得到的结果与标准RDME模型以及(更详细的)基于粒子的布朗动力学模拟进行比较。通过一个多目标优化问题来定义和研究误差和数值成本对隔室大小的依赖性。