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Andreas Kremling

Researcher at Technische Universität München

Publications -  88
Citations -  5435

Andreas Kremling is an academic researcher from Technische Universität München. The author has contributed to research in topics: Biology & Pseudomonas putida. The author has an hindex of 23, co-authored 77 publications receiving 5062 citations. Previous affiliations of Andreas Kremling include Max Planck Society.

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Engineering sucrose metabolism in Pseudomonas putida highlights the importance of porins.

TL;DR: A new, so far uncharacterized gene cluster for sucrose metabolism from Pseudomonas protegens Pf‐5 is evaluated and it enables P. putida to grow on sucrose as the sole carbon and energy source and concludes that the outer membrane can be a considerable barrier for substrate transport, depending on strain, genotype and culture conditions.
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Characterization of noise in multistable genetic circuits reveals ways to modulate heterogeneity.

TL;DR: The aim is to understand which dynamical features of a simple autoregulatory system determine its intrinsic noise level, and how they can be modified in order to regulate state-transitions, and develop graphical methods which support the intuitive design of regulatory circuits with a desired noise pattern.
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Trehalose production by Cupriavidus necator from CO2 and hydrogen gas.

TL;DR: In this work, the hydrogen-oxidizing bacterium Cupriavidus necator H16 was engineered for trehalose production from gaseous substrates and it was found that expression of the sugar efflux transporter A (setA) from Escherichia coli lead to a tre Halose leaky phenotype of C. necator.
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Computer-Aided Modeling of Chemical and Biological Systems: Methods, Tools, and Applications

TL;DR: Computer tools can support and accelerate the development and implementation of first-principle models for chemical and biological processes significantly and several application examples illustrate this in the contribution.
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Catabolite repression in Escherichia coli- a comparison of modelling approaches.

TL;DR: In this article, the relevance of methods and approaches concerning mathematical modelling in systems biology is discussed by assessing and comparing two comprehensive mathematical models that describe catabolite repression.