A benchmark-driven approach to reconstruct metabolic networks for studying cancer metabolism
Fig 11
Benchmark performance scores for algorithms under study.
Hierarchical clustering (Euclidean distance) of the scores each method received over different benchmarks. Three main clusters were identified: 1- GIMME, CORDA and mCADRE with an overall weak to moderate performance; 2- PRIME, TRFBA and pFBAc with strong performance in comparison tests, and 3- FASTCORE, INIT, iMAT and FASTCORMICS with strong performance in consistency tests. Numbers in column correspond to comparison (blue color) or consistency (red color) benchmarks: 1-growth rate, 2- metabolite uptake/secretion rates, 3- drug response, 4- essential genes, 5- enrichment of OG/TS/LOFs, 6- fraction of blocked reactions, 7- resolution power, 8- robustness to missing data, and 9- robustness to noise. Colorbar indicates normalized performance scores.