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A modeling approach of the chemostat

Authors: Fritsch, Coralie; Harmand, Jérôme; Campillo, Fabien;

A modeling approach of the chemostat

Abstract

Population dynamics and in particular microbial population dynamics, though they are complex but also intrinsically discrete and random, are conventionally represented as deterministic differential equations systems. We propose to revisit this approach by complementing these classic formalisms by stochastic formalisms and to explain the links between these representations in terms of mathematical analysis but also in terms of modeling and numerical simulations. We illustrate this approach on the model of chemostat.

arXiv admin note: substantial text overlap with arXiv:1308.2411

Country
France
Keywords

Stochastic chemostat model, Mass structured chemostat model, Populations and Evolution (q-bio.PE), [MATH] Mathematics [math], Quantitative Biology - Quantitative Methods, 510, FOS: Biological sciences, [MATH]Mathematics [math], Individually-based model (IBM), Quantitative Biology - Populations and Evolution, Monte Carlo, Quantitative Methods (q-bio.QM), Chemostat model

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
Green
bronze