A new class of highly efficient exact stochastic simulation algorithms for chemical reaction networks.

@article{Ramaswamy2009ANC,
  title={A new class of highly efficient exact stochastic simulation algorithms for chemical reaction networks.},
  author={Rajesh Ramaswamy and N{\'e}lido Gonz{\'a}lez-Segredo and Ivo F. Sbalzarini},
  journal={The Journal of chemical physics},
  year={2009},
  volume={130 24},
  pages={
          244104
        }
}
We introduce an alternative formulation of the exact stochastic simulation algorithm (SSA) for sampling trajectories of the chemical master equation for a well-stirred system of coupled chemical reactions. Our formulation is based on factored-out, partial reaction propensities. This novel exact SSA, called the partial-propensity direct method (PDM), is highly efficient and has a computational cost that scales at most linearly with the number of chemical species, irrespective of the degree of… 

Figures and Tables from this paper

A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays.
TLDR
The resulting delay partial-propensity direct method (dPDM) is an exact dSSA formulation for well-stirred systems of coupled chemical reactions with delays and is shown to be particularly efficient for strongly coupled reaction networks, where the number of reactions is much larger than thenumber of species.
Efficient Constant-Time Complexity Algorithm for Stochastic Simulation of Large Reaction Networks
TLDR
This work presents a new exact algorithm that employs the composition-rejection on the propensity bounds of reactions to select the next reaction firing and provides a favorable scaling for the computational complexity in simulating large reaction networks.
Exact on-lattice stochastic reaction-diffusion simulations using partial-propensity methods.
TLDR
The present algorithm, called partial-propensity stochastic reaction-diffusion (PSRD) method, uses an on-lattice discretization of the reaction- Diffusion system and relies on partial-Propensity methods for computational efficiency.
Constant-complexity Stochastic Simulation Algorithm with Optimal Binning
TLDR
This work describes an exact Stochastic Simulation Algorithm (SSA) that uses a table data structure with event time binning to achieve constant computational complexity with respect to the number of reaction channels for weakly coupled reaction networks.
An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems
TLDR
This study compares the efficiency and limitations of several available implementations of network-based and -free stochastic simulation approaches, to allow for an informed selection of the implementation and methodology for specific biochemical modeling applications.
Efficient stochastic simulation of biochemical reactions with noise and delays.
TLDR
This paper investigates new efficient formulations of the stochastic simulation algorithm to improve its computational efficiency and presents a new method for computing the firing time of the next reaction, based on recycling of random numbers.
A partial-propensity variant of the composition-rejection stochastic simulation algorithm for chemical reaction networks.
TLDR
The PSSA-CR thus combines the advantages of partial-propensity methods and the composition-rejection SSA, providing favorable scaling of the computational cost for all classes of reaction networks.
Selected-node stochastic simulation algorithm.
TLDR
The selected-node stochastic simulation algorithm (snSSA), which allows us to exclusively simulate an arbitrary, selected subset of molecular species of a possibly large and complex reaction network, based on an analytical elimination of chemical species, thereby avoiding explicit simulation of the associated chemical events.
Simulation of biochemical reactions with time-dependent rates by the rejection-based algorithm.
TLDR
The computation for selecting next reaction firings by the time-dependent RSSA (tRSSA) is computationally efficient and the generated trajectory is exact by exploiting the rejection-based mechanism.
...
...

References

SHOWING 1-10 OF 103 REFERENCES
A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks.
TLDR
A constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure is presented, which is applicable to kinetic Monte Carlo simulations in general and its competitive performance on small- and medium-size networks is demonstrated.
Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels
TLDR
The Next Reaction Method is presented, an exact algorithm to simulate coupled chemical reactions that uses only a single random number per simulation event, and is also efficient.
Approximate accelerated stochastic simulation of chemically reacting systems
TLDR
With further refinement, the τ-leap method should provide a viable way of segueing from the exact SSA to the approximate chemical Langevin equation, and thence to the conventional deterministic reaction rate equation, as the system size becomes larger.
Efficient formulation of the stochastic simulation algorithm for chemically reacting systems.
TLDR
It is concluded that for most practical problems the optimized direct method is the most efficient formulation of SSA, in contrast to the widely held belief that Gibson and Bruck's next reaction method.
Logarithmic Direct Method for Discrete Stochastic Simulation of Chemically Reacting Systems ∗
TLDR
This paper proposes a highly efficient formulation of SSA, with computational complexity that is independent of the ordering of the reactions, for realistic, practical biochemical systems.
Exact Stochastic Simulation of Coupled Chemical Reactions
There are two formalisms for mathematically describing the time behavior of a spatially homogeneous chemical system: The deterministic approach regards the time evolution as a continuous, wholly
K-leap method for accelerating stochastic simulation of coupled chemical reactions.
TLDR
This paper develops an alternative leap method called the K-leap method, in which the total number of reactions occurring during a leap is constrained to be a number K calculated from the leap condition, thereby improving simulation accuracy.
...
...