Additive functions in boolean models of gene regulatory network modules.

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Etat: Serval
Version: de l'auteur
ID Serval
serval:BIB_46BAD6D21823
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Additive functions in boolean models of gene regulatory network modules.
Périodique
Plos One
Auteur(s)
Darabos C., Di Cunto F., Tomassini M., Moore J.H., Provero P., Giacobini M.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Statut éditorial
Publié
Date de publication
2011
Volume
6
Numéro
11
Pages
e25110
Langue
anglais
Notes
Publication types: Journal ArticlePublication Status: ppublish
Résumé
Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.
Pubmed
Web of science
Open Access
Oui
Création de la notice
05/01/2012 17:34
Dernière modification de la notice
08/05/2019 17:58
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