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Résumé
A class of generic models of protocells is introduced, which are inspired by the 'Los Alamos bug' hypothesis but which, due to their abstraction level, can be applied to a wider set of detailed protocell hypotheses.These models describe the coupled growth of the lipid container and of the selfreplicating molecules.A technique to analyze the dynamics of populations of such protocells is described, which couples a continuoustime formalism for the growth between two successive cell divisions, and a discrete map which relates the quantity of selfreplicating molecules in successive generations.This technique allows one to derive several properties in an analytical way.It is shown that,under fairly general assumptions,the two growth rates synchronize,so that the lipid container doubles its size when the quantity of selfreplicating molecules has also doubled'thus giving rise to exponential growth of the population of protocells.Such synchronization had been postulated a priori in previous models of protocells,while it is here an emergent property.We also compare the rate of duplication of two populations generated by two different protocells with different kinds of selfreplicating molecules,considering the interesting case where the rate of selfreplication of one kind is higher than that of the other,but its contribution to the container growth rate is smaller.It is shown that in this case the population of offsprings of the protocell with the faster replicating molecule will eventually grow faster than the other.The case where two different types of selfreplicating monomers are present in the same protocell is also analyzed, and it is shown that,if the replication follows a first order kinetic equation, then the faster replicator eventually displaces the slower one,while if the growth is sublinear the two coexist.It is also proven by an appropriate rescaling of time that the results which concern the system asymptotic dynamics hold both for micelles and vesicles.
langue originale  Anglais 

Pages (de  à)  123138 
Nombre de pages  16 
journal  Artificial Life 
Volume  13 
Numéro de publication  2 
Etat de la publication  Publié  2007 
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