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Stephen J. Van Dien

Researcher at Genomatica

Publications -  32
Citations -  4010

Stephen J. Van Dien is an academic researcher from Genomatica. The author has contributed to research in topics: Polyphosphate & Polyphosphate kinase. The author has an hindex of 18, co-authored 31 publications receiving 3580 citations. Previous affiliations of Stephen J. Van Dien include University of California, Berkeley.

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Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli

TL;DR: The data and analyses presented here highlight the ability to identify organizing metabolic principles from systems-level absolute metabolite concentration data, and facilitate efficient flux reversibility given thermodynamic and osmotic constraints.
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Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol

TL;DR: This work engineered the E. coli host to enhance anaerobic operation of the oxidative tricarboxylic acid cycle, thereby generating reducing power to drive the BDO pathway, leading to a strain of Escherichia coli capable of producing 18 g l(-1) of this highly reduced, non-natural chemical.
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Development of a commercial scale process for production of 1,4-butanediol from sugar.

TL;DR: A sustainable bioprocess for the production of 1,4-butanediol from carbohydrate feedstocks was developed and an overall process that successfully performed at commercial scale for direct production of bio-BDO from dextrose is highlighted.
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From the first drop to the first truckload: commercialization of microbial processes for renewable chemicals.

TL;DR: In this paper, the authors present the challenges in reaching commercial titer, yield, and productivity targets, along with other necessary strain and process characteristics, and present a strategy for using these tools to overcome the major hurdles on the path to commercialization.
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Metabolic flux elucidation for large-scale models using 13C labeled isotopes.

TL;DR: A computational framework that combines a constraint-based modeling framework with isotopic label tracing on a large scale is presented that investigates the importance of carrying out isotopic labeling studies using a more comprehensive reaction network including global metabolite balances on cofactors such as ATP, NADH, and NADPH.