Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics

By Eric L. Haseltine, James B. Rawlings. 2002

595 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/840d28400587f52bce77dba48a9b2a68ae1a62c2

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In Biomedical Engineering

In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

Control, exploitation and tolerance of intracellular noise (2002, methodology): “Yet other approach is to construct hybrid models involving continuous and discrete representation”
Fokker–Planck approximation of the master equation in molecular biology (2009, unknown): “[5],[18].”
Separation of time-scales and model reduction for stochastic reaction networks. (2010, methodology): “Papers by Rao and Arkin (2003) and Haseltine and Rawlings (2002) stimulated considerable interest in this approach and notable contributions by Cao, Gillespie, and Petzold (2005), Goutsias (2005), E, Liu, and Vanden-Eijnden (2007), Mastny, Haseltine, and Rawlings (2007), Crudu, Debussche, and…”
An overview of spatial microscopic and accelerated kinetic Monte Carlo methods (2007, methodology): “Time scale separation among various processes (stiffness; low and large barriers) Diffusion too fast in comparison to surface reactions; multiple diffusion paths with different barriers Net-event MC method [73];b Probability-weighted MC method [75];c Rescaling of probabilities [76];d Partial equilib”
Stochastic approaches for modelling in vivo reactions (2004, background): “Accordingly, Haseltine and Rawlings (2002) attempt to speed up the performance of the SSA by partitioning a chemical reaction system into slow and fast reaction subsets.”
Stochastic delay differential equations for genetic regulatory networks (2007, unknown): “on the chemical master equation [12].”
Direct Solution of the Chemical Master Equation Using Quantized Tensor Trains (2014, methodology): “This class includes the Moment Closure methods [11,12], the Linear Noise Approximation (LNA) [13], and Chemical Langevin Equation (CLE) treatments [14,15].”
Convergence of stochastic gene networks to hybrid piecewise deterministic processes (2011, background): “Markov processes approaches to gene networks dynamics, originating from the pioneering ideas of Delbrück [Delbrück (1940)], capture diverse features of the experimentally observed expression variability, such as bursting [Cai, Friedman and Xie (2006)], various types of steady-state distributions of ”
A Dynamical Low-Rank Approach to the Chemical Master Equation (2008, methodology): “As a remedy, approximate techniques have been suggested based on tau-leaping or partitioning of the system [17, 36, 7, 5, 18, 37, 34, 20, 1, 38, 6, 10].”