Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

doi:10.1371/journal.pcbi.1004838

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

Fig 9

A comparison of the ¹³C-MFA flux, the flux predicted by ML only, and the flux predicted by MFlux in Case 16.

G. thermoglucosidasius M10EXG was incubated in sealed bottles (micro-aerobic condition), supplied with glucose as a carbon source. Detailed information is in S2 Table.

doi: https://doi.org/10.1371/journal.pcbi.1004838.g009