The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior

2006 ◽  
Vol 30 (1) ◽  
pp. 39-49 ◽  
Author(s):  
James M. McCollum ◽  
Gregory D. Peterson ◽  
Chris D. Cox ◽  
Michael L. Simpson ◽  
Nagiza F. Samatova
Keyword(s):  
Stochastic Simulation ◽  
Direct Method ◽  
Biochemical Systems

scholarly journals Numerical studies of higher order tau-leaping methods

2021 ◽  
Author(s):  
Anuj Dhoj Thapa
Keyword(s):  
Stochastic Simulation ◽  
Computational Cost ◽  
Practical Interest ◽  
Stochastic Simulation Algorithm ◽  
Simulation Method ◽  
Equation Model ◽  
Fast Reactions ◽  
Biochemical Systems ◽  
Computationally Intensive ◽  
Reacting Systems

Gillespie's algorithm, also known as the Stochastic Simulation Algorithm (SSA), is an exact simulation method for the Chemical Master Equation model of well-stirred biochemical systems. However, this method is computationally intensive when some fast reactions are present in the system. The tau-leap scheme developed by Gillespie can speed up the stochastic simulation of these biochemically reacting systems with negligible loss in accuracy. A number of tau-leaping methods were proposed, including the explicit tau-leaping and the implicit tau-leaping strategies. Nonetheless, these schemes have low order of accuracy. In this thesis, we investigate tau-leap strategies which achieve high accuracy at reduced computational cost. These strategies are tested on several biochemical systems of practical interest.

scholarly journals Stochastic Simulation of Biochemical Systems: In Memory of Dan T. Gillespie’s contributions

2019 ◽  
Vol 81 (8) ◽  
pp. 2819-2821
Author(s):  
Yang Cao ◽  
Petzold Linda ◽  
Effrosyni Seitaridou
Keyword(s):  
Stochastic Simulation ◽  
Biochemical Systems

scholarly journals StochKit2: software for discrete stochastic simulation of biochemical systems with events

2011 ◽  
Vol 27 (17) ◽  
pp. 2457-2458 ◽  
Author(s):  
K. R. Sanft ◽  
S. Wu ◽  
M. Roh ◽  
J. Fu ◽  
R. K. Lim ◽  
...  
Keyword(s):  
Stochastic Simulation ◽  
Biochemical Systems

scholarly journals Numerical studies of higher order tau-leaping methods

2021 ◽  
Author(s):  
Anuj Dhoj Thapa
Keyword(s):  
Stochastic Simulation ◽  
Computational Cost ◽  
Practical Interest ◽  
Stochastic Simulation Algorithm ◽  
Simulation Method ◽  
Equation Model ◽  
Fast Reactions ◽  
Biochemical Systems ◽  
Computationally Intensive ◽  
Reacting Systems

Gillespie's algorithm, also known as the Stochastic Simulation Algorithm (SSA), is an exact simulation method for the Chemical Master Equation model of well-stirred biochemical systems. However, this method is computationally intensive when some fast reactions are present in the system. The tau-leap scheme developed by Gillespie can speed up the stochastic simulation of these biochemically reacting systems with negligible loss in accuracy. A number of tau-leaping methods were proposed, including the explicit tau-leaping and the implicit tau-leaping strategies. Nonetheless, these schemes have low order of accuracy. In this thesis, we investigate tau-leap strategies which achieve high accuracy at reduced computational cost. These strategies are tested on several biochemical systems of practical interest.

scholarly journals Effective Time-Stepping For The Tau-Leaping Method for Stochastic Simulation Of Well-Stirred Biochemical Networks

2021 ◽  
Author(s):  
Mahmuda Binte Mostofa Ruma
Keyword(s):  
Mathematical Models ◽  
Stochastic Simulation ◽  
Practical Interest ◽  
Cellular Level ◽  
Biochemical Networks ◽  
Biological Processes ◽  
Time Stepping ◽  
Effective Time ◽  
Numerical Tests ◽  
Biochemical Systems

Biological processes at the cellular level are noisy. The noise arises due to random molecular collisions, and may be substantial in systems with low molecular counts in some species. This thesis introduces a variable tau-leaping method for the simulation of stochastic discrete mathematical models of well-stirred biochemical systems which is theoretically justified. Numerical tests on several models of biochemical systems of practical interest illustrate the advantages of the adaptive tau-leap method over the existing schemes.

scholarly journals Guided proposals for efficient weighted stochastic simulation

2019 ◽  
Author(s):  
Colin S. Gillespie ◽  
Andrew Golightly
Keyword(s):  
Stochastic Simulation ◽  
Importance Sampling ◽  
Rare Event ◽  
Jump Process ◽  
Jump Processes ◽  
Superior Performance ◽  
Markov Jump ◽  
Process Representation ◽  
Biochemical Systems ◽  
Recent Developments

AbstractRare event probabilities play an important role in the understanding of the behaviour of biochemical systems. Due to the intractability of the most natural Markov jump process representation of a system of interest, rare event probabilities are typically estimated using importance sampling. While the resulting algorithm is reasonably well developed, the problem of choosing a suitable importance density is far from straightforward. We therefore leverage recent developments on simulation of conditioned jump processes to propose an importance density that is simple to implement and requires no tuning. Our results demonstrate superior performance over some existing approaches.

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