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Modelling autocatalytic networks with artificial microbiology
Authors:Demarty Maurice  Gleyse Bernard  Raine Derek  Ripoll Camille  Norris Vic
Affiliation:Laboratoire des processus intégratifs cellulaires, UPRESA CNRS 6037, faculté des sciences et techniques de Rouen, 76821 Mont-Saint-Aigan, France. Maurice.Demarty@univ-rouen.fr
Abstract:Cells can usefully be equated to autocatalytic networks that increase in mass and then divide. To begin to model relationships between autocatalytic networks and cell division, we have written a program of artificial chemistry that simulates a cell fed by monomers. These monomers are symbols that can be assembled into linear (non-branched) polymers to give different lengths. A reaction is catalysed by a particular polymer or 'enzyme' that may itself be a reactant of that reaction (autocatalysis). These reactions are only studied within the confines of the 'cell' or 'reaction chamber'. There is a flux of material through the cell and eventually the mass of polymers reaches a threshold at which we analyse the cell. Our results indicate a similarity between the connectivity of the reaction network and that of real metabolic networks. Developing the model will entail attributing increased probabilities of reactions to polymers that are colocalised to evaluate the consequences of the dynamics of large assemblies of diverse molecules (hyperstructures) and of cell division.
Keywords:artificial chemistry  autocatalytic networks  hyperstructures  chimie artificielle  réseaux autocatalytiques  hyperstructures  modélisation
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