The aim of metabolic flux analysis is the quantitative determination of as many intracellular reaction fluxes as possible in a system of interest. Nonstationary metabolic flux analysis (NMFA) applies dynamic measurements of isotopic labeling in intracellular metabolites to a complex computational model in order to obtain these fluxes.

We have applied elementary metabolite unit (EMU) theory to NMFA, dramatically reducing the computational difficulty of the problem. This improvement has led to a 1500-fold reduction in computational times, enabling a new and more complicated set of problems to be analyzed with NMFA. In this study, we investigate the flux network of Saccharomyces cerevisae. Using measurements of isotopic labeling of intracellular amino acids and organic acids, we have estimated metabolic fluxes and metabolite concentrations in a genetically perturbed strain relative to a control strain.