ArticleBulletin of mathematical biology2019
Generalizing Gillespie's Direct Method to Enable Network-Free Simulations.
Article in Bulletin of mathematical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Parameter Estimation and Uncertainty Quantification for Systems Biology Models.Current opinion in systems biology · 2019Article
- Article
- Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks.The Journal of chemical physics · 2019Article
- MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor.PLoS computational biology · 2019Article
- A Probabilistic Model of the Germinal Center Reaction.Frontiers in immunology · 2019Article
- Intrinsic limits of information transmission in biochemical signalling motifs.Interface focus · 2018Article
- Using Equation-Free Computation to Accelerate Network-Free Stochastic Simulation of Chemical Kinetics.The journal of physical chemistry. B · 2018Article
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6 authors.
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Abstract
Gillespie's direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie's direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termed network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie's direct method for network-free simulation. Finally, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.
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