The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Stochastic Simulation of Chemical Kinetics
Abstract
Stochastic chemical kinetics describes the time evolution of a well-stirred chemically reacting system in a way that takes into account the fact that molecules come in whole numbers and exhibit some degree of randomness in their dynamical behavior. Researchers are increasingly using this approach to chemical kinetics in the analysis of cellular systems in biology, where the small molecular populations of only a few reactant species can lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. After reviewing the supporting theory of stochastic chemical kinetics, I discuss some recent advances in methods for using that theory to make numerical simulations. These include improvements to the exact stochastic simulation algorithm (SSA) and the approximate explicit tau-leaping procedure, as well as the development of two approximate strategies for simulating systems that are dynamically stiff: implicit tau-leaping and the slow-scale SSA.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
Exact stochastic simulation of coupled chemical reactions
Gillespie, D. T. (1977) · The Journal of Physical Chemistry · doi:10.1021/j100540a008 · Cited by 10,136
Self-citationNumerical Recipes, The Art of Scientific Computing
Press, W. H., Flannery, B. P., Teukolsky, S. A., Vetterling, W. T., & Gould, H. (1987) · American Journal of Physics · doi:10.1119/1.14981 · Cited by 10,024
Numerical Recipes: The Art of Scientific Computing
Ziegel, E. (1987) · Technometrics · doi:10.1080/00401706.1987.10488304 · Cited by 6,702
Gillespie, D. T. (1976) · Journal of Computational Physics · doi:10.1016/0021-9991(76)90041-3 · Cited by 6,029
Self-citationStochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441
Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations
Ascher, U. M., & Petzold, L. R. (1998) · doi:10.1137/1.9781611971392 · Cited by 2,403 · cited 3×
“A well-known strategy for numerically solving a stiff ODE dx / dt = f (x) is to replace the explicit updating formula xt+� t = xt + f (xt)� t with an implicit formula, such as xt+� t = xt + f (xt + � t)� t ( 36 ).”
BackgroundMethodInfluentialApproximate accelerated stochastic simulation of chemically reacting systems
Gillespie, D. T. (2001) · The Journal of Chemical Physics · doi:10.1063/1.1378322 · Cited by 1,884
Self-citationStochastic mechanisms in gene expression
McAdams, H. H., & Arkin, A. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.3.814 · Cited by 1,847
Noise in eukaryotic gene expression
Blake, W. J., KÆrn, M., Cantor, C. R., & Collins, J. J. (2003) · Nature · doi:10.1038/nature01546 · Cited by 1,667
Cited by
Modelling and analysis of gene regulatory networks
Karlebach, G., & Shamir, R. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2503 · Cited by 1,296
Aerosol Mixing State: Measurements, Modeling, and Impacts
Riemer, N., Ault, A. P., West, M., Craig, R. L., & Curtis, J. H. (2019) · Reviews of Geophysics · doi:10.1029/2018rg000615 · Cited by 459
Barr, A. R., Cooper, S., Heldt, F. S., Butera, F., Stoy, H., Mansfeld, J., Novák, B., & Bakal, C. (2017) · Nature Communications · doi:10.1038/ncomms14728 · Cited by 403
Fundamental limits on dynamic inference from single-cell snapshots
Weinreb, C., Wolock, S., Tusi, B. K., Socolovsky, M., & Klein, A. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714723115 · Cited by 341
From the stochasticity of molecular processes to the variability of synaptic transmission
Ribrault, C., Sekimoto, K., & Triller, A. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3025 · Cited by 198
Metadata
- Authors
- Gillespie, D. T.
- Venue
- Annual Review of Physical Chemistry
- Publisher
- Annual Reviews
- Published
- 2007-05-01
- Volume
- 58
- Issue
- 1
- Pages
- 35-55
- ISSN
- 0066-426X (ISSN-L)
- 1545-1593
- OpenAlex
- W2167154952
- Cited by
- 2,115
- References
- 40
- FWCI
- 2.45
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Stochastic Simulation of Chemical Kinetics. https://app.cochat.ai/papers/10.1146/annurev.physchem.58.032806.104637
- The paper
- Gillespie, D. T. (2007). Stochastic Simulation of Chemical Kinetics. Annual Review of Physical Chemistry. https://doi.org/10.1146/annurev.physchem.58.032806.104637
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
