Bayesian inference of metabolic kinetics from genome-scale multiomics data
Fig 4
Parameterizing a genome-scale kinetic model with multiomics data.
(A) Distributions in log-transformed (unitless) experimental data after normalizing with respect to the phosphate-limited reference state. (B) Posterior predictive distributions after fitting with ADVI. Higher weight was given to experimental datapoints close to the reference state (±1.5) as indicated by the gray boxes. (C) Heat map of correlation coefficient between experimental enzyme measurements (x-axis) and experimental boundary flux measurements. Boundary fluxes and enzymes are sorted with hierarchical clustering. (D) Heat map of FCC as estimated from posterior parameter distributions. Boundary flux and enzyme ordering match those determined in (C). Colors represent medians of the posterior predictive distributions, FCCs with a direction that could not be confidently determined are colored white.