Document Detail


A stochastic model of autocatalytic reaction networks.
MedLine Citation:
PMID:  21979857     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Autocatalytic cycles are rather widespread in nature and in several theoretical models of catalytic reaction networks their emergence is hypothesized to be inevitable when the network is or becomes sufficiently complex. Nevertheless, the emergence of autocatalytic cycles has been never observed in wet laboratory experiments. Here, we present a novel model of catalytic reaction networks with the explicit goal of filling the gap between theoretical predictions and experimental findings. The model is based on previous study of Kauffman, with new features in the introduction of a stochastic algorithm to describe the dynamics and in the possibility to increase the number of elements and reactions according to the dynamical evolution of the system. Furthermore, the introduction of a temporal threshold allows the detection of cycles even in our context of a stochastic model with asynchronous update. In this study, we describe the model and present results concerning the effect on the overall dynamics of varying (a) the average residence time of the elements in the reactor, (b) both the composition of the firing disk and the concentration of the molecules belonging to it, (c) the composition of the incoming flux.
Authors:
Alessandro Filisetti; Alex Graudenzi; Roberto Serra; Marco Villani; Rudolf M Füchslin; Norman Packard; Stuart A Kauffman; Irene Poli
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-10-7
Journal Detail:
Title:  Theory in biosciences = Theorie in den Biowissenschaften     Volume:  -     ISSN:  1611-7530     ISO Abbreviation:  -     Publication Date:  2011 Oct 
Date Detail:
Created Date:  2011-10-7     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9708216     Medline TA:  Theory Biosci     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
European Centre for Living Technology, Calle del Clero 2940, 30124, Venice, Italy, alessandro.filisetti@ecltech.org.
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