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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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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Chemical Master Equation ; Moment Equations ; Stochastic Modeling
ISSN (print) / ISBN
2405-8963
e-ISSN
1474-6670
Konferenztitel
19th World Congress of the International Federation of Automatic Control (IFAC)
Konferzenzdatum
24 - 29 August 2014
Konferenzort
Cape Town, South Africa
Zeitschrift
IFAC-PapersOnLine
Quellenangaben
Band: 19,
Seiten: 1729-1735
Verlag
Elsevier
Verlagsort
Frankfurt ; München [u.a.]
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Computational Biology (ICB)