In this report we review the Riedel-Bruck stochastic simulation algorithm, which makes use of a cycle-leaping strategy to improve the simulation performance. We implemented the algorithmi and tested our implementation on some stochastic models, such as the Lotka-Volterra model of predation, the Brusselator model, and the Michaelis-Menten model of enzymatic catalysis. We discuss the advantages and the disadvantages of this algorithm from the viewpoint of its use in a systemic approach to modeling and simulation of biochemical and biological processes
textBiochemical reactions make up most of the activity in a cell. There is inherent stochasticity in...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
In this dissertation, we introduce a novel accelerated-stochastic simulation method, known as the ‘p...
In this report we review the Riedel-Bruck stochastic simulation algorithm, which makes use of a cycl...
The stochastic simulation algorithm (SSA), first proposed by Gillespie, has become the workhorse of ...
In this paper we give an overview of some very recent work on the stochastic simulation of systems i...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
Computational techniques provide invaluable tools for developing a quantitative understanding the co...
Recent studies through biological experiments have indicated that noise plays a very important role ...
A growing realisation of the importance of stochasticity in cell and molecular processes has stimula...
Traditionally, the law of mass action has been used to deterministically model chemical reactions. T...
Publication costs assisted by the Naval Weapons Center There are two formalisms for mathematically d...
Original paper can be found at: http://www.sciencedirect.com/science/bookseries/00766879 Copyright E...
This paper discusses new simulation algorithms for stochastic chemical kinetics that exploit the lin...
Abstract reaction event that occurs in the system, the accuracy of the method comes at a high comput...
textBiochemical reactions make up most of the activity in a cell. There is inherent stochasticity in...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
In this dissertation, we introduce a novel accelerated-stochastic simulation method, known as the ‘p...
In this report we review the Riedel-Bruck stochastic simulation algorithm, which makes use of a cycl...
The stochastic simulation algorithm (SSA), first proposed by Gillespie, has become the workhorse of ...
In this paper we give an overview of some very recent work on the stochastic simulation of systems i...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
Computational techniques provide invaluable tools for developing a quantitative understanding the co...
Recent studies through biological experiments have indicated that noise plays a very important role ...
A growing realisation of the importance of stochasticity in cell and molecular processes has stimula...
Traditionally, the law of mass action has been used to deterministically model chemical reactions. T...
Publication costs assisted by the Naval Weapons Center There are two formalisms for mathematically d...
Original paper can be found at: http://www.sciencedirect.com/science/bookseries/00766879 Copyright E...
This paper discusses new simulation algorithms for stochastic chemical kinetics that exploit the lin...
Abstract reaction event that occurs in the system, the accuracy of the method comes at a high comput...
textBiochemical reactions make up most of the activity in a cell. There is inherent stochasticity in...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
In this dissertation, we introduce a novel accelerated-stochastic simulation method, known as the ‘p...