Parallel isotope differential modeling for instationary 13C fluxomics at the genome scale.

ABSTRACT:

Background

A precise map of the metabolic fluxome, the closest surrogate to the physiological phenotype, is becoming progressively more important in the metabolic engineering of photosynthetic organisms for biofuel and biomass production. For photosynthetic organisms, the state-of-the-art method for this purpose is instationary 13C fluxomics, which has arisen as a sibling of transcriptomics or proteomics. Instationary 13C data processing requires solving high-dimensional nonlinear differential equations and leads to large computational and time costs when its scope is expanded to a genome-scale metabolic network.

Result

Here, we present a parallelized method to model instationary 13C labeling data. The elementary metabolite unit (EMU) framework is reorganized to allow treati

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC7278083 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature