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Modeling of stochastic biological processes with non-polynomial propensities using non-central conditional moment equation.
IFAC PapersOnline 19, 1729-1735 (2014)
Biological processes exhibiting stochastic fluctuations are mainly modeled using the Chemical Master Equation (CME). As a direct simulation of the CME is often computationally intractable, we recently introduced the Method of Conditional Moments (MCM). The MCM is a hybrid approach to approximate the statistics of the CME solution. In this work, we provide a more comprehensive formulation of the MCM by using non-central conditional moments instead of central conditional moments. The modified formulation allows for additional insight into the model structure and for extensions to higher-order reactions and non-polynomial propensity functions. The properties of the non-central MCM are analyzed using a model for the regulation of pili formation on the surface of bacteria, which possesses rational propensity functions.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Chemical Master Equation ; Moment Equations ; Stochastic Modeling
ISSN (print) / ISBN
2405-8963
e-ISSN
1474-6670
Conference Title
19th World Congress of the International Federation of Automatic Control (IFAC)
Conference Date
24 - 29 August 2014
Conference Location
Cape Town, South Africa
Journal
IFAC-PapersOnLine
Quellenangaben
Volume: 19,
Pages: 1729-1735
Publisher
Elsevier
Publishing Place
Frankfurt ; München [u.a.]
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)