COAST: Controllable approximative stochastic reaction algorithm

Wagner H, Moeller M, Prank K (2006)
JOURNAL OF CHEMICAL PHYSICS 125(17).

Journal Article | Published | English

No fulltext has been uploaded

Author
; ;
Abstract
We present an approximative algorithm for stochastic simulations of chemical reaction systems, called COAST, based on three different modeling levels: for small numbers of particles an exact stochastic model; for intermediate numbers an approximative, but computationally more efficient stochastic model based on discrete Gaussian distributions; and for large numbers the deterministic reaction kinetics. In every simulation time step, the subdivision of the reaction channels into the three different modeling levels is done automatically, where all approximations applied can be controlled by a single error parameter for which an appropriate value can easily be found. Test simulations show that the results of COAST simulations agree well with the outcomes of exact algorithms; however, the asymptotic run times of COAST are asymptotically proportional to smaller powers of the particle numbers than exact algorithms. (c) 2006 American Institute of Physics.
Publishing Year
ISSN
PUB-ID

Cite this

Wagner H, Moeller M, Prank K. COAST: Controllable approximative stochastic reaction algorithm. JOURNAL OF CHEMICAL PHYSICS. 2006;125(17).
Wagner, H., Moeller, M., & Prank, K. (2006). COAST: Controllable approximative stochastic reaction algorithm. JOURNAL OF CHEMICAL PHYSICS, 125(17).
Wagner, H., Moeller, M., and Prank, K. (2006). COAST: Controllable approximative stochastic reaction algorithm. JOURNAL OF CHEMICAL PHYSICS 125.
Wagner, H., Moeller, M., & Prank, K., 2006. COAST: Controllable approximative stochastic reaction algorithm. JOURNAL OF CHEMICAL PHYSICS, 125(17).
H. Wagner, M. Moeller, and K. Prank, “COAST: Controllable approximative stochastic reaction algorithm”, JOURNAL OF CHEMICAL PHYSICS, vol. 125, 2006.
Wagner, H., Moeller, M., Prank, K.: COAST: Controllable approximative stochastic reaction algorithm. JOURNAL OF CHEMICAL PHYSICS. 125, (2006).
Wagner, Holger, Moeller, Mark, and Prank, Klaus. “COAST: Controllable approximative stochastic reaction algorithm”. JOURNAL OF CHEMICAL PHYSICS 125.17 (2006).
This data publication is cited in the following publications:
This publication cites the following data publications:

3 Citations in Europe PMC

Data provided by Europe PubMed Central.

Spatial aspects in biological system simulations.
Resat H, Costa MN, Shankaran H., Meth. Enzymol. 487(), 2011
PMID: 21187236
Quantifying stochastic effects in biochemical reaction networks using partitioned leaping.
Harris LA, Piccirilli AM, Majusiak ER, Clancy P., Phys Rev E Stat Nonlin Soft Matter Phys 79(5 Pt 1), 2009
PMID: 19518479

19 References

Data provided by Europe PubMed Central.

Modelling cellular behaviour.
Endy D, Brent R., Nature 409(6818), 2001
PMID: 11201753
Modeling of signaling networks.
Neves SR, Iyengar R., Bioessays 24(12), 2002
PMID: 12447976
Inside a living cell.
Goodsell DS., Trends Biochem. Sci. 16(6), 1991
PMID: 1891800

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
Hybrid simulation of cellular behavior.
Kiehl TR, Mattheyses RM, Simmons MK., Bioinformatics 20(3), 2004
PMID: 14960457

AUTHOR UNKNOWN, 0
A multi-algorithm, multi-timescale method for cell simulation.
Takahashi K, Kaizu K, Hu B, Tomita M., Bioinformatics 20(4), 2004
PMID: 14990450
Grid cellware: the first grid-enabled tool for modelling and simulating cellular processes.
Dhar PK, Meng TC, Somani S, Ye L, Sakharkar K, Krishnan A, Ridwan AB, Wah SH, Chitre M, Hao Z., Bioinformatics 21(7), 2005
PMID: 15546936

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
Mechanisms of noise-resistance in genetic oscillators.
Vilar JM, Kueh HY, Barkai N, Leibler S., Proc. Natl. Acad. Sci. U.S.A. 99(9), 2002
PMID: 11972055

Box, Ann. Math. Stat. 29(), 1958

AUTHOR UNKNOWN, 0

Buchner, Elemente der Mathematik 6(), 1951

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Sources

PMID: 17100426
PubMed | Europe PMC

Search this title in

Google Scholar