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Robert G. Egbert
Researcher at Pacific Northwest National Laboratory
Publications - 24
Citations - 401
Robert G. Egbert is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Biology & Synthetic biology. The author has an hindex of 7, co-authored 17 publications receiving 324 citations. Previous affiliations of Robert G. Egbert include Lawrence Berkeley National Laboratory & University of Washington.
Papers
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Posted ContentDOI
Resource reallocation in engineered Escherichia coli strains with reduced genomes
Ernesto S. Nakayasu,Adam M. Chazin-Gray,Ryan M. Francis,Arielle Eaton,Deanna L. Auberry,Nathalie Munoz,Joseph A. Cottam,Jeremy Zucker,Neeraj Kumar,Carrie D. Nicora,Hugh D. Mitchell,Young-Mo Kim,William C. Nelson,Robert G. Egbert +13 more
TL;DR: An amino acid metabolism imbalance and compromised growth that were correlated with elimination of genes associated with significant proteome fraction were identified and exhibited decreased stability of PDV production compared to the wild-type strain under persistent PDV expression conditions despite the alleviation of fitness defects.
Posted ContentDOI
Sorgoleone degradation by sorghum-associated bacteria; an opportunity for enforcing plant growth promotion
Yasuhiro Oda,Joshua R. Elmore,William C. Nelson,Andrew Stewart. Wilson,Yuliya Farris,Dean J. Pettinga,Aaron J. Ogden,Henri Baldino,Adam M. Deutschbauer,Catalina Vega Hurtado,Jason E. McDermott,Adam M. Guss,Devin Coleman-Derr,Ryan McClure,Caroline S. Harwood,Robert G. Egbert +15 more
TL;DR: In this paper , the molecular determinants of microbial sorgoleone degradation and the distribution of this trait among microbes were identified and studied from sorghum-associated soils, three bacterial strains classified as Acinetobacter, Burkholderia, and Pseudomonas species that grow with sorghleone as a sole carbon and energy source.
Journal ArticleDOI
Data-Driven Observability Decomposition with Koopman Operators for Optimization of Output Functions of Nonlinear Systems
TL;DR: In this article , the authors extend the notion of nonlinear observable decomposition to the more general class of data-informed systems and employ Koopman operator theory, which encapsulates nonlinear dynamics in linear models, allowing to bridge the gap between linear and nonlinear observability notions.
Posted Content
Prediction of fitness in bacteria with causal jump dynamic mode decomposition
Shara Balakrishnan,Aqib Hasnain,Nibodh Boddupalli,Dennis M. Joshy,Robert G. Egbert,Enoch Yeung +5 more
TL;DR: In this article, a generic data-driven framework for training operator-theoretic models to predict cell growth rate was introduced, and the experimental design and data generated in this study, namely growth curves of Pseudomonas putida as a function of casein and glucose concentrations.
Dissertation
Fine-tuning Engineered Gene Regulatory Networks Expressed in Escherichia coli using Hypervariable Simple Sequence Repeats
TL;DR: This dissertation presents a methodology to fine-tune engineered gene networks in Escherichia coli that accelerates the realization of functionally complex behaviors using focused variation to thoroughly sample gene expression levels for a target network.