IGM: Integrated Gene-expression Modeling for multi-condition flux-preserving genome-scale metabolic models
Fig 2
Performance comparison of IGM, FBA, and regularized variants.
(A-B) Predictive accuracy of IGM, FBA, and their L1/L2 regularized variants, evaluated by correlation coefficient (A) and normalized root mean square error (NRMSE) (B) between predicted fluxes and experimentally measured fluxes across three E. coli datasets (Data-A, Data-B, and Data-C). IGM consistently shows higher correlation and lower NRMSE compared to FBA. Regularization further improves performance, with L1 yielding the most stable and accurate predictions. (C) Reaction flux flexibility ratio between IGM and FBA across metabolic subsystems. Ratios ≤ 1 indicate that IGM reduces or maintains solution space relative to FBA, thereby refining flux predictions and improving reliability.