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Despite the significant progress made in recent years, the computation of thecomplete set of elementary flux modes of large or even genome-scale metabolicnetworks is still impossible. We introduce a novel approach to speed up thecalculation of elementary flux modes by including transcriptional regulatoryinformation into the analysis of metabolic network. Taking into account generegulation dramatically reduces the solution space and allows the presentedalgorithm to constantly eliminate biologically infeasible modes at an earlystage of the computation procedure. Thereby, the computational costs, such asruntime, memory usage and disk space are considerably reduced. Consequently,using the presented mode elimination algorithm pushes the size of metabolicnetworks that can be studied by elementary flux modes to new limits.

Utilizing gene regulatory information to speed up the calculation of elementary flux modes