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http://dx.doi.org/10.18419/opus-10821
Autor(en): | Eisenkolb, Ina Jensch, Antje Eisenkolb, Kerstin Kramer, Andrei Buchholz, Patrick C. F. Pleiss, Jürgen Spiess, Antje Radde, Nicole |
Titel: | Modeling of biocatalytic reactions: a workflow for model calibration, selection, and validation using Bayesian statistics |
Erscheinungsdatum: | 2019 |
Dokumentart: | Zeitschriftenartikel |
Seiten: | 13, 7 |
Erschienen in: | AIChE journal 66 (2020), e16866 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-108383 http://elib.uni-stuttgart.de/handle/11682/10838 http://dx.doi.org/10.18419/opus-10821 |
ISSN: | 1547-5905 |
Zusammenfassung: | We present a workflow for kinetic modeling of biocatalytic reactions which combines methods from Bayesian learning and uncertainty quantification for model calibration, model selection, evaluation, and model reduction in a consistent statistical frame-work. Our workflow is particularly tailored to sparse data settings in which a considerable variability of the parameters remains after the models have been adapted to available data, a ubiquitous problem in many real-world applications. Our workflow is exemplified on an enzyme-catalyzed two-substrate reaction mechanism describing the symmetric carboligation of 3,5-dimethoxy-benzaldehyde to (R)-3,3',5,5'-tetramethoxybenzoin catalyzed by benzaldehyde lyase from Pseudomonas fluorescens. Results indicate a substrate-dependent inactivation of enzyme, which is in accordance with other recent studies. |
Enthalten in den Sammlungen: | 07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
---|---|---|---|---|
Eisenkolbetal_2020_Modeling_of_biocatalytic_reactions.pdf | Article | 3,6 MB | Adobe PDF | Öffnen/Anzeigen |
Eisenkolbetal_2020_Modeling_of_biocatalytic_reactions_Suppl.pdf | Supporting information | 3,46 MB | Adobe PDF | Öffnen/Anzeigen |
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