HIGHLIGHTS
- who: from the DepartmentUniversity of have published the article: Identification of Genome-Scale Metabolic Network Models Using Experimentally Measured Flux Profiles, in the Journal: (JOURNAL)
- what: The approach used required careful manual evaluation of the mispredictions, and in many cases clear reasons for incorrect predictions could not be identified. In this paper the development and application of computational methods for optimal metabolic network identification (OMNI) based on in_vivo measured growth rate, exchange flux (substrate uptake and byproduct secretion rate), and intracellular flux data is described. The authors focus exclusively on applying OMNI to experimentally evolved . . .
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