Planning isotopomer measurements for estimation of metabolic fluxes
Flux estimation by using isotopomer information of metabolites is currently the only method that can give quantitative estimates of the activity of metabolic pathways. However, the measurement of isotopomer distributions of intermediate metabolites is costly and tedious with current technologies. In this paper we study the question of finding the smallest subset of metabolites to measure that ensure an adequate level of the isotopomer information. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give exact and fast heuristic solutions and evaluate empirically the efficacy of the proposed methods.