. Author manuscript; available in PMC: 2019 Oct 5.

Published in final edited form as: Curr Opin Biotechnol. 2019 Mar 7;59:24–30. doi: 10.1016/j.copbio.2019.02.005

Table 1.

Applicability of mechanistic and data-driven metabolic modeling and inference frameworks

Key: [] = N/A [] = Low [] = Medium [**] = High		Applicability of framework in providing insights regarding:						Resource availability
Key: [] = N/A [] = Low [] = Medium [**] = High		Metabolic engineering strategies		Regulatory structure inference
	Framework name	Rate-limiting steps	State prediction	Metabolite-level	Transcriptional	Metabolic stability	Kinetic variation	Experimental	Computational	Scalability	Recent applications
Mechanistic, targeted	EM-RA	**	***	*		***	**	***	**	**	[16,17^•]
	ABC-GRASP	***	***	**		**	**	***	*	*	[5]
	ORACLE+ IMCA	***	*		*	*	**	**	***	**	[8]
	ORACLE+ iSCHRUNK	***	*			*	**	***	***	**	[7]
	MASS	*	*			*	***	**	***	***	[18,20]
Data-driven, untargeted	LiP-SMap			***				**	***	***	[12^••]
	Fuhrer [13]			**	**			*	***	***	[13]
	Kochanowski [14^•]				***			*	***	***	[14^•]
	SIMMER			***				*	***	***	[11]
	Costello [57^••]	***	***	*	*			*	**	***	[57^••]