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 3

Overview of central metabolic fluxes collected in our dataset.

“Flux range” represents the variation of each flux in the ¹³C-MFA dataset. “95% confidence interval” indicates that 95% of flux data were within a small range. “Average flux value” is the average value in each flux based on all data in our ¹³C-MFA dataset.

doi: https://doi.org/10.1371/journal.pcbi.1004838.g003