A benchmark-driven approach to reconstruct metabolic networks for studying cancer metabolism
Fig 8
Normalized growth prediction of GEMs generated using data from repeated 5-fold cross-validation.
(A) CORDA, (B) FASTCORE, (C) FASTCORMICS, (D) GIMME, (E) mCADRE, (F) PRIME, (G) TRFBA, (H) iMAT. Only algorithms capable of predicting growth are shown. For each algorithm, “model count” represents the GEMs generated by incomplete expression data or core reactions set in the input. For a better comparison, growth rates were normalized to the maximum value.