Twelve quick tips for designing sound dynamical models for bioprocesses

Because of the inherent complexity of bioprocesses, mathematical models are more and more used for process design, control, optimization, etc. These models are generally based on a set of biochemical reactions. Model equations are then derived from mass balance, coupled with empirical kinetics. Biol...

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Vydáno v:PLoS computational biology Ročník 15; číslo 8; s. e1007222
Hlavní autoři: Mairet, Francis, Bernard, Olivier
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Public Library of Science 22.08.2019
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ISSN:1553-7358, 1553-734X, 1553-7358
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Shrnutí:Because of the inherent complexity of bioprocesses, mathematical models are more and more used for process design, control, optimization, etc. These models are generally based on a set of biochemical reactions. Model equations are then derived from mass balance, coupled with empirical kinetics. Biological models are nonlinear and represent processes, which by essence are dynamic and adaptive. The temptation to embed most of the biology is high, with the risk that calibration would not be significant anymore. The most important task for a modeler is thus to ensure a balance between model complexity and ease of use. Since a model should be tailored to the objectives, which will depend on applications and environment, a universal model representing any possible situation is probably not the best option.
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The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1007222