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Author Demongeot, J.; Goles, E.; Morvan, M.; Noual, M.; Sene, S. pdf  doi
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  Title (up) Attraction Basins as Gauges of Robustness against Boundary Conditions in Biological Complex Systems Type
  Year 2010 Publication Plos One Abbreviated Journal PLoS One  
  Volume 5 Issue 8 Pages 18 pp  
  Keywords  
  Abstract One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally.  
  Address [Demongeot, Jacques] Univ Grenoble 1, TIMC IMAG, CNRS, UMR 5525, La Tronche, France, Email: Sylvain.Sene@ibisc.univ-evry.fr  
  Corporate Author Thesis  
  Publisher Public Library Science Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1932-6203 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000280605400002 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 92  
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