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BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
View ORCID ProfileTyler W. H. Backman, Christina Schenk, Tijana Radivojevic, David Ando, Janavi Singh, Jeffrey J. Czajka, Zak Costello, Jay D. Keasling, Yinjie Tang, Elena Akhmatskaya, View ORCID ProfileHector Garcia Martin
doi: https://doi.org/10.1101/2023.04.19.537435
Tyler W. H. Backman
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
Christina Schenk
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
3BCAM, Basque Center for Applied Mathematics, 48009 Bilbao, Spain
4DOE Agile BioFoundry, Emeryville, CA, 94608, USA
Tijana Radivojevic
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
4DOE Agile BioFoundry, Emeryville, CA, 94608, USA
David Ando
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
Janavi Singh
11Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
Jeffrey J. Czajka
5Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
Zak Costello
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
4DOE Agile BioFoundry, Emeryville, CA, 94608, USA
Jay D. Keasling
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
6Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA
7Department of Bioengineering, University of California, Berkeley, CA 94720, USA
8QB3 Institute, University of California, Berkeley, CA 94720, USA
9Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark 2800 Copenhagen, Denmark
10Center for Synthetic Biochemistry, Institute for Synthetic Biology, Shenzhen Institutes for Advanced Technologies, Shenzhen, China
Yinjie Tang
5Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA
Elena Akhmatskaya
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
3BCAM, Basque Center for Applied Mathematics, 48009 Bilbao, Spain
12IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain
Hector Garcia Martin
1Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
2Biofuels and Bioproducts Division, Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA
3BCAM, Basque Center for Applied Mathematics, 48009 Bilbao, Spain
4DOE Agile BioFoundry, Emeryville, CA, 94608, USA
Article usage
Posted April 20, 2023.
BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
Tyler W. H. Backman, Christina Schenk, Tijana Radivojevic, David Ando, Janavi Singh, Jeffrey J. Czajka, Zak Costello, Jay D. Keasling, Yinjie Tang, Elena Akhmatskaya, Hector Garcia Martin
bioRxiv 2023.04.19.537435; doi: https://doi.org/10.1101/2023.04.19.537435
BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
Tyler W. H. Backman, Christina Schenk, Tijana Radivojevic, David Ando, Janavi Singh, Jeffrey J. Czajka, Zak Costello, Jay D. Keasling, Yinjie Tang, Elena Akhmatskaya, Hector Garcia Martin
bioRxiv 2023.04.19.537435; doi: https://doi.org/10.1101/2023.04.19.537435
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