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Computation 2018, 6(1), 9; https://doi.org/10.3390/computation6010009

An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems

Center for Quantitative Medicine and Department of Cell Biology, University of Connecticut School of Medicine, 263 Farmington Av., Farmington, CT 06030-6033, USA
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Received: 9 December 2017 / Revised: 23 January 2018 / Accepted: 29 January 2018 / Published: 31 January 2018
(This article belongs to the Section Computational Biology)
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Abstract

Stochastic simulation has been widely used to model the dynamics of biochemical reaction networks. Several algorithms have been proposed that are exact solutions of the chemical master equation, following the work of Gillespie. These stochastic simulation approaches can be broadly classified into two categories: network-based and -free simulation. The network-based approach requires that the full network of reactions be established at the start, while the network-free approach is based on reaction rules that encode classes of reactions, and by applying rule transformations, it generates reaction events as they are needed without ever having to derive the entire network. In this study, we compare the efficiency and limitations of several available implementations of these two approaches. The results allow for an informed selection of the implementation and methodology for specific biochemical modeling applications. View Full-Text
Keywords: stochastic simulation; modeling; network-based; network-free; rule-based modeling; systems biology stochastic simulation; modeling; network-based; network-free; rule-based modeling; systems biology
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Gupta, A.; Mendes, P. An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems. Computation 2018, 6, 9.

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