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dc.contributor.authorVillegas, Pabloes_ES
dc.contributor.authorRuiz-Franco, Josées_ES
dc.contributor.authorHidalgo Aguilera, Jorgees_ES
dc.contributor.authorMuñoz Martínez, Miguel Ángel es_ES
dc.date.accessioned2017-02-10T12:21:29Z
dc.date.available2017-02-10T12:21:29Z
dc.date.issued2016
dc.identifier.citationVillegas, P.; et al. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks. Scientific Reports, 6: 34743 (2016). [http://hdl.handle.net/10481/44773]es_ES
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10481/44773
dc.description.abstractGene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way –even for asynchronous updating rules– and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.en_EN
dc.description.sponsorshipSpanish-MINECO grant FIS2013-43201-P (FEDER funds) for financial supporten_EN
dc.language.isoenges_ES
dc.publisherNature Publishing Groupes_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.subjectGene regulatory networksen_EN
dc.subjectBoolean networksen_EN
dc.subjectBioinformaticsen_EN
dc.subjectGene expressionen_EN
dc.subjectNoise en_EN
dc.titleIntrinsic noise and deviations from criticality in Boolean gene-regulatory networksen_EN
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1038/srep34743


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