BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
About this item
Full title
Author / Creator
Backman, Tyler W. H. , Schenk, Christina , Radivojevic, Tijana , Ando, David , Singh, Jahnavi , Czajka, Jeffrey J. , Costello, Zak , Keasling, Jay D. , Tang, Yinjie , Akhmatskaya, Elena , Garcia Martin, Hector , Ouzounis, ed., Christos A. and Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Publisher
United States: Public Library of Science (PLoS)
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science (PLoS)
Subjects
More information
Scope and Contents
Contents
Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function.
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C Metabolic Flux Analysis (
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C MFA) is considered to be the gold standard for measuring metabolic fluxes.
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C MFA typically works by leveraging extracellular exc...
Alternative Titles
Full title
BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale
Authors, Artists and Contributors
Author / Creator
Schenk, Christina
Radivojevic, Tijana
Ando, David
Singh, Jahnavi
Czajka, Jeffrey J.
Costello, Zak
Keasling, Jay D.
Tang, Yinjie
Akhmatskaya, Elena
Garcia Martin, Hector
Ouzounis, ed., Christos A.
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_osti_scitechconnect_2217552
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_osti_scitechconnect_2217552
Other Identifiers
ISSN
1553-7358
E-ISSN
1553-7358
