Table 1 Classification of methods for EFM reduction

Network connectivity and stoichiometry

K-shortest EFM: Enumerates the EFM in increasing order of number of reactions.

Yield Analysis: Excludes EFM with negligible contribution to convex hull in yield space.

Parameter free

[11]

[12]

Thermodynamics

Fractional contributions of EFM: Estimates the EFM Coefficients based on calculated EFM thermodynamic properties.

Maximum Entropy Principle: Calculates the EFM Coefficient by maximizing Shannon's entropy, which is an indirect measure of system complexity.

Thermodynamic data

[13]

[14]

(Non)linear programming

α-spectrum: Uses linear optimization to maximize and minimize the weightings of each metabolic pathway that produces steady state flux distributions.

Flux regulation coefficients: Estimates the EFM coefficients that optimize a given performance function (e.g. minimum error in flux or yield prediction).

Quadratic program: Calculates the weights for a large set of EFM by using quadratic program to reconstruct flux distributions from subsets of EFM.

'-omics' data can be used to shrink the α-spectrum.

Fluxomics and possibly other omic datasets

[15, 16, 38]

[18]

[17]

Enzyme kinetics

Quantitative elementary mode analysis of metabolic pathways: Combines structural and kinetic modelling to assess the effect of changes in enzyme kinetics on the usage of EFM.

Enzyme kinetic parameters

[19]