Zobrazeno 1 - 10
of 124
pro vyhledávání: '"Brian F Pfleger"'
Autor:
Wai Kit Ong, Dylan K Courtney, Shu Pan, Ramon Bonela Andrade, Patricia J Kiley, Brian F Pfleger, Jennifer L Reed
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 8, p e1008137 (2020)
Genome-scale metabolic models have been utilized extensively in the study and engineering of the organisms they describe. Here we present the analysis of a published dataset from pooled transposon mutant fitness experiments as an approach for improvi
Externí odkaz:
https://doaj.org/article/48c82c973d924b5f838a270e4307c3c3
Publikováno v:
Microbial Biotechnology, Vol 17, Iss 11, Pp n/a-n/a (2024)
Abstract Microorganisms in large‐scale bioreactors are exposed to heterogeneous environmental conditions due to physical mixing constraints. Nutritional gradients can lead to transient expression of energetically wasteful stress responses and as a
Externí odkaz:
https://doaj.org/article/e533765a5fcb4a8eb15efc97cbf7e125
Autor:
Rebecca M Lennen, Brian F Pfleger
Publikováno v:
PLoS ONE, Vol 8, Iss 1, p e54031 (2013)
Microbial synthesis of free fatty acids (FFA) is a promising strategy for converting renewable sugars to advanced biofuels and oleochemicals. Unfortunately, FFA production negatively impacts membrane integrity and cell viability in Escherichia coli,
Externí odkaz:
https://doaj.org/article/65bbd79267f2431fb6c5b6e0ed2334e2
Autor:
Matthew B Begemann, Erin K Zess, Eric M Walters, Emily F Schmitt, Andrew L Markley, Brian F Pfleger
Publikováno v:
PLoS ONE, Vol 8, Iss 10, p e76594 (2013)
Cyanobacteria are valuable organisms for studying the physiology of photosynthesis and carbon fixation, as well as metabolic engineering for the production of fuels and chemicals. This work describes a novel counter selection method for the cyanobact
Externí odkaz:
https://doaj.org/article/acd17325ef6749d58ac88b8b42584c03
Publikováno v:
Bioengineering, Vol 11, Iss 9, p 892 (2024)
In recent years, the design–build–test–learn (DBTL) cycle has become a key concept in strain engineering. Modern biofoundries enable automated DBTL cycling using robotic devices. However, both highly automated facilities and semi-automated faci
Externí odkaz:
https://doaj.org/article/780a77adf7f84ce9bd4d210c0f1a87e6
Autor:
Michael A. Jindra, Kisurb Choe, Ratul Chowdhury, Ryan Kong, Soodabeh Ghaffari, Jonathan V. Sweedler, Brian F. Pfleger
Publikováno v:
Metabolic Engineering. 77:21-31
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::736a98b32755a688e77458b632f08a22
https://doi.org/10.1016/j.ymben.2023.02.012
https://doi.org/10.1016/j.ymben.2023.02.012
Autor:
Dylan K. Courtney, Yun Su, Tyler B. Jacobson, Daven B. Khana, Aditya Ailiani, Daniel Amador-Noguez, Brian F. Pfleger
Publikováno v:
ACS Catalysis. 13:5914-5925
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0f1c0704478c2a457c729b0af3b9c71
https://doi.org/10.1021/acscatal.3c00379
https://doi.org/10.1021/acscatal.3c00379
Autor:
Qiang Yan, Tyler B. Jacobson, Zhou Ye, Yoel R. Cortés-Pena, Sarang S. Bhagwat, Susan Hubbard, William T. Cordell, Rebecca E. Oleniczak, Francesca V. Gambacorta, Julio Rivera Vazquez, Eric V. Shusta, Daniel Amador-Noguez, Jeremy S. Guest, Brian F. Pfleger
Publikováno v:
Metabolic Engineering. 76:18-28
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1249eab314b1e62602928087e28d938
https://doi.org/10.1016/j.ymben.2023.01.003
https://doi.org/10.1016/j.ymben.2023.01.003
Autor:
Francesca V. Gambacorta, Ellen R. Wagner, Tyler B. Jacobson, Mary Tremaine, Laura K. Muehlbauer, Mick A. McGee, Justin J. Baerwald, Russell L. Wrobel, John F. Wolters, Mike Place, Joshua J. Dietrich, Dan Xie, Jose Serate, Shabda Gajbhiye, Lisa Liu, Maikayeng Vang-Smith, Joshua J. Coon, Yaoping Zhang, Audrey P. Gasch, Daniel Amador-Noguez, Chris Todd Hittinger, Trey K. Sato, Brian F. Pfleger
Publikováno v:
Synthetic and Systems Biotechnology. 7:738-749
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ddf1a80342a4d1c1afc8756167289f2
https://doi.org/10.1016/j.synbio.2022.02.007
https://doi.org/10.1016/j.synbio.2022.02.007
Publikováno v:
Current Research in Biotechnology, Vol 4, Iss, Pp 1-9 (2022)
Classification of proteins into their respective functional categories remains a long-standing key challenge in computational biology. Machine Learning (ML) based discriminative algorithms have been used extensively to address this challenge; however
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82381d5a6f178ee6b46710da04cfe688
https://doi.org/10.1016/j.crbiot.2021.12.002
https://doi.org/10.1016/j.crbiot.2021.12.002