Stochastic simulation of biochemical systems: in memory of Dan T. Gillespie's contributions
From MaRDI portal
Publication:2325557
DOI10.1007/s11538-019-00633-wzbMath1476.00108OpenAlexW2955370423WikidataQ91538509 ScholiaQ91538509MaRDI QIDQ2325557
No author found.
Publication date: 26 September 2019
Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11538-019-00633-w
Proceedings, conferences, collections, etc. pertaining to probability theory (60-06) Collections of articles of miscellaneous specific interest (00B15) Proceedings, conferences, collections, etc. pertaining to numerical analysis (65-06) Festschriften (00B30) Proceedings, conferences, collections, etc. pertaining to biology (92-06)
Cites Work
- Multiscale stochastic simulation algorithm with stochastic partial equilibrium assumption for chemically reacting systems
- Variance-reduced simulation of lattice discrete-time Markov chains with applications in reaction networks
- Generalizing Gillespie's direct method to enable network-free simulations
- Stochastic dynamics of eukaryotic flagellar growth
- The linear noise approximation for spatially dependent biochemical networks
- Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions
- Quasi-Monte Carlo methods applied to tau-leaping in stochastic biological systems
- Spatial stochastic intracellular kinetics: a review of modelling approaches
- Stochastic simulation of pattern formation in growing tissue: a multilevel approach
- Accuracy analysis of hybrid stochastic simulation algorithm on linear chain reaction systems
- A critical comparison of rejection-based algorithms for simulation of large biochemical reaction networks
- \(S\)-leaping: an adaptive, accelerated stochastic simulation algorithm, bridging \(\tau\)-leaping and \(R\)-leaping
- Data-driven method for efficient characterization of rare event probabilities in biochemical systems
- Sensitivity analysis for multiscale stochastic reaction networks using hybrid approximations
- Multiscale stochastic reaction-diffusion algorithms combining Markov chain models with stochastic partial differential equations