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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao HAL INRAEarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Part of book or chapter of book . 2015
Data sources: HAL INRAE
https://doi.org/10.1007/978-94...
Part of book or chapter of book . 2014 . Peer-reviewed
Data sources: Crossref
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Modeling in Microbial Ecology

Authors: Poggiale, Jean-Christophe; Dantigny, Philippe; de Wit, Rutger; Steinberg, Christian;

Modeling in Microbial Ecology

Abstract

The bases and the principles of modeling in microbial community ecology and biogeochemistry are presented and discussed. Several examples are given. Among them, the fermentation process is largely developed, thus demonstrating how the model allows determining the microbial population growth rate, the death rate, and the maintenance rate. More generally, these models have been used to increase the development of bioenergetic formulations which are presently used in biogeochemical models (Monod, Droop, DEB models). Different types of interactions (competition, predation, and virus–bacteria) are also developed. For each topic, a complete view of the models used in the literature cannot be presented. Consequently, the focus has been done on the demonstration how to build a model instead of providing a long list of existing models. Some recent results in sediment biogeochemistry are provided to illustrate the application of such models.

Keywords

[SDE] Environmental Sciences, chemostat, [SDV]Life Sciences [q-bio], 500, biofilm models, 510, biotic interactions, [SDV] Life Sciences [q-bio], [SDE]Environmental Sciences, population dynamics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, fermenter models, metabolic models, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology

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    citations
    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).
    4
    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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Found an issue? Give us feedback
citations
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!
4
Average
Average
Average
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