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dc.rights.licensehttp://creativecommons.org/licenses/by/4.0es_MX
dc.creatorRUBEN YVAN MAARTEN FOSSIONes_MX
dc.creatorDIEGO ANDRES HARTASANCHEZ FRENKes_MX
dc.creatorOSBALDO RESENDIS ANTONIOes_MX
dc.creatorALEJANDRO FRANK HOEFLICHes_MX
dc.date2013-
dc.date.accessioned2021-10-28T17:00:44Z-
dc.date.available2021-10-28T17:00:44Z-
dc.identifier.urihttp://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17283-
dc.descriptionComplex systems from different fields of knowledge often do not allow a mathematical description or modeling, because of their intricate structure composed of numerous interacting components. As an alternative approach, it is possible to study the way in which observables associated with the system fluctuate in time. These time series may provide valuable information about the underlying dynamics. It has been suggested that complex dynamic systems, ranging from ecosystems to financial markets and the climate, produce generic early-warning signals at the “tipping points,” where they announce a sudden shift toward a different dynamical regime, such as a population extinction, a systemic market crash, or abrupt shifts in the weather. On the other hand, the framework of Self-Organized Criticality (SOC), suggests that some complex systems, such as life itself, may spontaneously converge toward a critical point. As a particular example, the quasispecies model suggests that RNA viruses self-organize their mutation rate near the error-catastrophe threshold, where robustness and evolvability are balanced in such a way that survival is optimized. In this paper, we study the time series associated to a classical discrete quasispecies model for different mutation rates, and identify early-warning signals for critical mutation rates near the error-catastrophe threshold, such as irregularities in the kurtosis and a significant increase in the autocorrelation range, reminiscent of 1/f noise. In the present context, we find that the early-warning signals, rather than broadcasting the collapse of the system, are the fingerprint of survival optimization.es_MX
dc.formatAdobe PDFes_MX
dc.languageenges_MX
dc.publisherSpringer Verlag & Higher Education Presses_MX
dc.relationhttps://link.springer.com/article/10.1007/s11515-013-1256-0es_MX
dc.relation.requiresSies_MX
dc.rightsAcceso Abiertoes_MX
dc.sourceFrontiers in Biology (1674-7992) Vol. 8 (2013)es_MX
dc.subjectBIOLOGÍA Y QUÍMICAes_MX
dc.subjectCiencias de la vidaes_MX
dc.subjectGenéticaes_MX
dc.subjectGenética clínicaes_MX
dc.subjectFenómenos genéticoses_MX
dc.subjectVariación genéticaes_MX
dc.subjectQuiasispecieses_MX
dc.subject1/f noisees_MX
dc.subjectGeneticses_MX
dc.subjectGenetic phenomenaes_MX
dc.subjectGenetic variationes_MX
dc.titleCriticality, adaptability and early-warning signals in time series in a discrete quasispecies modeles_MX
dc.typeArtículoes_MX
dc.audienceResearcherses_MX
dc.creator.idFOXR771115HNESXB09es_MX
dc.creator.idHAFD821120HDFRRG01es_MX
dc.creator.idREAO710324HMSSNS05es_MX
dc.creator.idFAHA510804HNLRFL05es_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
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