The concept of elementary flux vector is valuable in a number of applications of metabolic engineering. For instance, in metabolic flux analysis, each admissible flux vector can be expressed as a non-negative linear combination of a small number of elementary flux vectors. However a critical issue concerns the total number of elementary flux vectors which may be huge because it combinatorially increases with the size of the metabolic network. In this paper we present a fast algorithm that randomly computes a decomposition of admissible flux vectors in a minimal number of elementary flux modes without explicitly enumerating all of them. The method is illustrated with an experimental case-study on CHO cells where the network has 65329 elementary flux vectors while the admissible flux distributions are expressed as a combination of 22 elementary vectors only.
Raphaël M. Jungers, Francisca Zamorano, Vince