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Bas Teusink

Researcher at VU University Amsterdam

Publications -  208
Citations -  12497

Bas Teusink is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Metabolic network & Saccharomyces cerevisiae. The author has an hindex of 56, co-authored 193 publications receiving 10872 citations. Previous affiliations of Bas Teusink include University of Amsterdam & Delft University of Technology.

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Mice Expressing Only the Mutant APOE3Leiden Gene Show Impaired VLDL Secretion

TL;DR: The results show that APOE3Leiden does not prevent development of a fatty liver and does not normalize VLDL-TG secretion in mice with an apoE-deficient background, and it is concluded that apOE-mediated stimulation of V LDL secretion is isoform specific.
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Strategies for structuring interdisciplinary education in systems biology: An European perspective

TL;DR: One of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling.
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Multi-way analysis of flux distributions across multiple conditions

TL;DR: With the availability of genome sequences of many organisms and information about gene‐protein‐reaction (GPR) associations with respect to these organisms genome‐scale metabolic networks can be reconstructed, and reactions that are functionally coherent are expected to highly correlate in terms of their flux value over different flux distributions.
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Genome-Scale Metabolic Reconstruction of Acetobacter pasteurianus 386B, a Candidate Functional Starter Culture for Cocoa Bean Fermentation

TL;DR: The reconstruction of the A. pasteurianus 386B genome-scale metabolic model revealed knowledge gaps concerning the metabolism of this strain, especially related to the biosynthesis of its cell envelope and the presence or absence of metabolite transporters.
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Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

TL;DR: A computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49, using genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis to find strategies to reduce the growth of the pathogen and propose drug targets.