Dynamical robustness of biological networks with hierarchical distribution of time scales

Alexander Gorban 1 Ovidiu Radulescu 2, 3, *
* Corresponding author
2 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We analyze the concepts of distributed robustness and r-robustness proposed by biologists to explain a variety of stability phenomena in molecular biology. Then we discuss the robustness of the relaxation time using a chemical reaction description of genetic and signalling networks. First, we obtain the following result for linear networks: for large multiscale systems with hierarchical distribution of time scales the variance of the inverse relaxation time (as well as the variance of the stationary rate) is much lower than the variance of the separate constants. Moreover, it can tend to 0 faster than 1/n, where n is the number of reactions. We argue that similar phenomena are valid in the nonlinear case as well. As a numerical illustration we use a model of signalling network for the important transcription factor NFkB
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https://hal.inria.fr/inria-00181450
Contributor : Ovidiu Radulescu <>
Submitted on : Tuesday, October 23, 2007 - 6:55:34 PM
Last modification on : Friday, November 16, 2018 - 1:25:18 AM

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  • HAL Id : inria-00181450, version 1

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Alexander Gorban, Ovidiu Radulescu. Dynamical robustness of biological networks with hierarchical distribution of time scales. IET Systems Biology, Institution of Engineering and Technology, 2007. ⟨inria-00181450⟩

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