ArticleComputation (Basel, Switzerland)2018
An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems.
Article in Computation (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Catalyst: Fast and flexible modeling of reaction networks.PLoS computational biology · 2023Article
- SBbadger: biochemical reaction networks with definable degree distributions.Bioinformatics (Oxford, England) · 2022Article
- BiPSim: a flexible and generic stochastic simulator for polymerization processes.Scientific reports · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- Article
- Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer.NPJ systems biology and applications · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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.
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