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Autocatalytic genetic networks modeled by piecewise-deterministic Markov processes.
J. Math. Biol. 60, 207-246 (2010)
In the present work we propose an alternative approach to model autocatalytic networks, called piecewise-deterministic Markov processes. These were originally introduced by Davis in 1984. Such a model allows for random transitions between the active and inactive state of a gene, whereas subsequent transcription and translation processes are modeled in a deterministic manner. We consider three types of autoregulated networks, each based on a positive feedback loop. It is shown that if the densities of the stationary distributions exist, they are the solutions of a system of equations for a one-dimensional correlated random walk. These stationary distributions are determined analytically. Further, the distributions are analyzed for different simulation periods and different initial concentration values by numerical means. We show that, depending on the network structure, beside a binary response also a graded response is observable.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
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1.695
1.120
9
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Anmerkungen
Besondere Publikation
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Autocatalytic network; Markov process; Stationary distributions; Correlated random walk
Sprache
englisch
Veröffentlichungsjahr
2010
HGF-Berichtsjahr
2010
ISSN (print) / ISBN
0303-6812
e-ISSN
1432-1416
Zeitschrift
Journal of Mathematical Biology
Quellenangaben
Band: 60,
Heft: 2,
Seiten: 207-246
Verlag
Springer
Verlagsort
New York, NY
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Biomathematics and Biometry (IBB)
POF Topic(s)
30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
PSP-Element(e)
G-503800-001
PubMed ID
19326119
Scopus ID
74049117430
Erfassungsdatum
2010-12-31