MomentClosure.jl: automated moment closure approximations in Julia.
Open accessAbstract
Summary: MomentClosure.jl is a Julia package providing automated derivation of the time-evolution equations of the moments of molecule numbers for virtually any chemical reaction network using a wide range of moment closure approximations. It extends the capabilities of modelling stochastic biochemical systems in Julia and can be particularly useful when exact analytic solutions of the chemical master equation are unavailable and when Monte Carlo simulations are computationally expensive. Availability and implementation: MomentClosure.jl is freely accessible under the MIT licence. Source code and documentation are available at https://github.com/augustinas1/MomentClosure.jl.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Existing open-source biological modeling projects have extended Catalyst's intermediate representation.
“Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.”
From Catalyst: Fast and flexible modeling of reaction networks (2023) · cites this paper as [54]
Section 2.1 (page unavailable) says MomentClosure.jl is compatible with models defined in Catalyst.jl, and Section 2.2 describes generating moment equations from those models. This supports an example of a biological modeling project building on Catalyst, but our copy does not say that it extends Catalyst’s intermediate representation. (LLM, conf=0.78)
Experimental — accuracy not yet measuredIndependent package developers already utilise Catalyst's extensibility.
“Indeed, this is already being utilised by independent package developers.”
From Catalyst: Fast and flexible modeling of reaction networks (2023) · cites this paper as [54]
MomentClosure.jl is built to be deployed on Catalyst models.
“The MomentClosure.jl Julia package, which implements several techniques for moment closure approximations, is built to be deployed on Catalyst models [54].”
From Catalyst: Fast and flexible modeling of reaction networks (2023) · cites this paper as [54]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 18
Research works printed but not linked: 12
- Ale A. et al (2013) A general moment expansion method for stochastic kinetic models. J. Chem. Phys., 138, 174101. 23656108
- Azunre P. et al (2011) Mass fluctuation kinetics: analysis and computation of equilibria and local dynamics. IET Syst. Biol., 5, 325– 335. 22129028
- Cao Z., Grima R. (2019) Accuracy of parameter estimation for auto-regulatory transcriptional feedback loops from noisy data. J. R. Soc. Interf., 16, 20180967. PMC6505555 30940028
- Fan S. et al (2016) MEANS: python package for moment expansion approximation, iNference and simulation. Bioinformatics, 32, 2863– 2865. 27153663 PMC5018365
- Gillespie C. (2009) Moment-closure approximations for mass-action models. IET Syst. Biol., 3, 52– 58. 19154084
- Hespanha J. (2008) Moment closure for biochemical networks. In: IEEE Proc. of the 3rd International Symposium on Communications, Control and Signal Processing, Malta. pp. 142– 147.
- Kazeroonian A. et al (2016) CERENA: ChEmical REaction Network Analyzer—a toolbox for the simulation and analysis of stochastic chemical kinetics. PLoS One, 11, e0146732. 26807911 PMC4726759
- Lakatos E. et al (2015) Multivariate moment closure techniques for stochastic kinetic models. J. Chem. Phys., 143, 094107. 26342359
- Pietzsch T. et al (2021) Compartor: a toolbox for the automatic generation of moment equations for dynamic compartment populations. Bioinformatics, btab058. 33538766 PMC8428613
- Schnoerr D. et al (2015) Comparison of different moment-closure approximations for stochastic chemical kinetics. J. Chem. Phys., 143, 185101. 26567686
- Schnoerr D. et al (2017) Approximation and inference methods for stochastic biochemical kinetics—a tutorial review. J. Phys. A: Math. Theor., 50, 093001.
- Soltani M. et al (2015) Conditional moment closure schemes for studying stochastic dynamics of genetic circuits. IEEE Trans. Biomed. Circuits Syst., 9, 518– 526. 26336146
- Authors
- Sukys, A., & Grima, R.
- Affiliations
- The Alan Turing Institute (GB)
- University of Edinburgh (GB)
- Corresponding author
- Sukys, Augustinas
- Grima, Ramon
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-06-25
- Volume
- 38
- Issue
- 1
- Pages
- 289-290
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC8696096
- OpenAlex
- W3163858189
- Cited by
- 0
- References
- 18
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- arXiv (Cornell University) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc)
- arXiv (Cornell University)
- Funders
- Alan Turing Institute Doctoral Studentship [EPSRC (EP/N510129/1)
- Leverhulme Trust (RPG-2018-423)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- moment closure, chemical reaction networks, chemical master equation, moment equations, Julia
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
