[图书][B] Stochastic modelling of reaction–diffusion processes
R Erban, SJ Chapman - 2020 - books.google.com
This practical introduction to stochastic reaction-diffusion modelling is based on courses
taught at the University of Oxford. The authors discuss the essence of mathematical methods …
taught at the University of Oxford. The authors discuss the essence of mathematical methods …
[HTML][HTML] Hybrid framework for the simulation of stochastic chemical kinetics
Stochasticity plays a fundamental role in various biochemical processes, such as cell
regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be …
regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be …
Multiscale stochastic reaction–diffusion algorithms combining Markov chain models with stochastic partial differential equations
Two multiscale algorithms for stochastic simulations of reaction–diffusion processes are
analysed. They are applicable to systems which include regions with significantly different …
analysed. They are applicable to systems which include regions with significantly different …
Noise-induced mixing and multimodality in reaction networks
We analyse a class of chemical reaction networks under mass-action kinetics involving
multiple time scales, whose deterministic and stochastic models display qualitative …
multiple time scales, whose deterministic and stochastic models display qualitative …
Solution of the chemical master equation by radial basis functions approximation with interface tracking
Background The chemical master equation is the fundamental equation of stochastic
chemical kinetics. This differential-difference equation describes temporal evolution of the …
chemical kinetics. This differential-difference equation describes temporal evolution of the …
Error analysis of diffusion approximation methods for multiscale systems in reaction kinetics
Several different methods exist for efficient approximation of paths in multiscale stochastic
chemical systems. Another approach is to use bursts of stochastic simulation to estimate the …
chemical systems. Another approach is to use bursts of stochastic simulation to estimate the …
A transformed path integral approach for solution of the Fokker–Planck equation
GM Subramaniam, P Vedula - Journal of Computational Physics, 2017 - Elsevier
A novel path integral (PI) based method for solution of the Fokker–Planck equation is
presented. The proposed method, termed the transformed path integral (TPI) method …
presented. The proposed method, termed the transformed path integral (TPI) method …
系统生物学中的随机微分方程数值仿真算法
牛原玲， 陈琳， 陈洛南 - 数学理论与应用, 2023 - mta.csu.edu.cn
系统生物学中的诸多现象, 如生物化学反应过程, 生态系统的演变, 传染病的传播等,
都可以用随机微分方程来描述. 由于考虑了随机因素的影响, 随机微分方程模型往往能比确定性 …
都可以用随机微分方程来描述. 由于考虑了随机因素的影响, 随机微分方程模型往往能比确定性 …
Adaptive density tracking by quadrature for stochastic differential equations
RA Moore, A Narayan - Applied Mathematics and Computation, 2022 - Elsevier
Density tracking by quadrature (DTQ) is a numerical procedure for computing solutions to
Fokker-Planck equations that describe probability densities for stochastic differential …
Fokker-Planck equations that describe probability densities for stochastic differential …
Accurate reduction of a model of circadian rhythms by delayed quasi steady state assumptions
T Vejchodský - arXiv preprint arXiv:1312.2825, 2013 - arxiv.org
Quasi steady state assumptions are often used to simplify complex systems of ordinary
differential equations in modelling of biochemical processes. The simplified system is …
differential equations in modelling of biochemical processes. The simplified system is …