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Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks.

J. Theor. Biol. 266, 436-448 (2010)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
We generalize random Boolean networks by softening the hard binary discretization into multiple discrete states. These multistate networks are generic models of gene regulatory networks, where each gene is known to assume a finite number of functionally different expression levels. We analytically determine the critical connectivity that separates the biologically unfavorable frozen and chaotic regimes. This connectivity is inversely proportional to a parameter which measures the heterogeneity of the update rules. Interestingly, the latter does not necessarily increase with the mean number of discrete states per node. Still, allowing for multiple states decreases the critical connectivity as compared to random Boolean networks, and thus leads to biologically unrealistic situations. Therefore, we study two approaches to increase the critical connectivity. First, we demonstrate that each network can be kept in its frozen regime by sufficiently biasing the update rules. Second, we restrict the randomly chosen update rules to a subclass of biologically more meaningful functions. These functions are characterized based on a thermodynamic model of gene regulation. We analytically show that their usage indeed increases the critical connectivity. From a general point of view, our thermodynamic considerations link discrete and continuous models of gene regulatory networks.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Dynamic systems on graphs; Multilevel logic; Thermodynamics; Transcriptional gene regulation
Sprache englisch
Veröffentlichungsjahr 2010
HGF-Berichtsjahr 2010
ISSN (print) / ISBN 0022-5193
e-ISSN 1095-8541
Quellenangaben Band: 266, Heft: 3, Seiten: 436-448 Artikelnummer: , Supplement: ,
Verlag Elsevier
Begutachtungsstatus Peer reviewed
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503700-001
PubMed ID 20654629
Scopus ID 77954968549
Erfassungsdatum 2010-12-31