User:Jarle Pahr/EFM

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Notes on Elementary Flux Modes:

Given a metabolic reaction network with stoichiometric matrix S, the steady state condition (no change in metabolite concentrations) is given by the equation

Sv = 0

The (right) nullspace of S contains all possible vectors v which fulfill this equation. The rank-nullity theorem states that the dimensions of the nullspace equals the number of columns in S minus the rank of S, which is denoted r. If all reactions are linearly independent and the number of reactions n is greater than the number of metabolites m, then r = m. All possible flux vectors in the nullspace of S can then be constructed by a linear combination of nm vectors spanning the nullspace. However, vectors spanning the nullspace may not be biologically meaningful and contain non-integer values, making it hard to interpret the nullspace. Elementary flux modes provide a basis for the nullspace which is easier to interpret.

Elementary flux modes decompose a metabolic network into components such that

  • Each component can operate in a steady state independently from the rest of metabolism
  • Any steady state can be described as a combination of such components

Any steady state flux vector can be described as a non-negative combination of the elementary flux modes, but the mapping need not be unique (several combinations might describe one flux vector).


Extreme pathways





EFMEvolver: Computing elementary flux modes in genome-scale metabolic networks:

Computing the shortest elementary flux modes in genome-scale metabolic networks:

Decomposing flux distributions into elementary flux modes in genome-scale metabolic networks:

Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering.:

Elementary flux modes in a nutshell: properties, calculation and applications.:

Analysis of Metabolic Subnetworks by Flux Cone Projection:

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