ICON-GEMs: integration of co-expression network in genome-scale metabolic models, shedding light through systems biology

Table 5 Predictive accuracy when applying various biological networks incorporating with the genome-scale metabolic model in S. cerevisiae

Acetoin	DataS1 (Own)	DataS2 (Microarray)	DataS3 (RNAseq)	PPI	Random (% of edges)			Random network
Acetoin	DataS1 (Own)	DataS2 (Microarray)	DataS3 (RNAseq)	PPI	25	50	75	Random network
0 mM	0.9074	0.8919	0.8922	0.9936	0.8909	0.8944	0.8248	0.8570
100 mM	0.9850	0.8961	0.9006	0.8948	0.8311	0.8115	0.8133	0.8047
200 mM	0.9872	0.8966	0.9079	0.8999	0.9010	0.8959	0.8842	0.8245
300 mM	0.9959	0.9019	0.9022	0.8998	0.8381	0.7941	0.8016	0.7945
Mean	0.9688	0.8966	0.9007	0.9221	0.8653	0.8490	0.8310	0.8201
Standard deviation	0.0357	0.0035	0.0055	0.0413	0.0310	0.0466	0.0318	0.0309

These conditions correspond to different concentrations of acetoin in S. cerevisiae; specifically, at 0 mM (as reference (RF)), 100 mM, 200 mM, and 300 mM

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