W
Wim Soetaert
Researcher at Ghent University
Publications - 240
Citations - 8921
Wim Soetaert is an academic researcher from Ghent University. The author has contributed to research in topics: Sophorolipid & Fermentation. The author has an hindex of 47, co-authored 227 publications receiving 7554 citations. Previous affiliations of Wim Soetaert include Schiller International University & Bio Base Europe.
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Microbial production and application of sophorolipids
Inge N. A. Van Bogaert,Karen Saerens,Cassandra De Muynck,Dirk Develter,Wim Soetaert,Erick Vandamme +5 more
TL;DR: An overview of the producing yeast strains and various aspects of fermentative sophorolipid production is given, and a summary is given on possible applications of sopharolipids, either as native or modified molecules.
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Leuconostoc dextransucrase and dextran: production, properties and applications
TL;DR: This review covers the production, properties and applications of the biopolysaccharide dextran; this biopolymer can be produced via fermentation either with Leuconostoc mesenteroides strains and other lactic acid bacteria or with certain Gluconobacter oxydans strains.
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Microbial metabolomics: past, present and future methodologies
Mlawule R. Mashego,Mlawule R. Mashego,Karl Rumbold,Marjan De Mey,Erick Vandamme,Wim Soetaert,Joseph J. Heijnen +6 more
TL;DR: This review focuses on the past, current and future development of various experimental protocols in the rapid developing area of metabolomics in the ongoing quest to reliably quantify microbial metabolites formed under defined physiological conditions.
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Microbial succinic acid production: Natural versus metabolic engineered producers
TL;DR: The state of the art of bio succinic acid production processes is critically evaluated in function of the production host, media, fermentation strategy, titers and yields.
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Construction and model-based analysis of a promoter library for E. coli: an indispensable tool for metabolic engineering
TL;DR: For Escherichia coli, the promoter strength can not been linked to anomalies in the -10 box and/or -35 box, and to the length of the spacer, but by applying Partial Least Squares regression, a good correlation was found between promoter sequence and promoter strength.