Inferring metabolic networks from metabolite concentration data is a central topic in systems biology. Mathematical techniques to extract information about the network from data have been proposed in the literature. This paper presents a critical assessment of the feasibility of reverse engineering of metabolic networks, illustrated with a selection of methods. Appropriate data are simulated to study the performance of four representative methods. An overview of sampling and measurement methods currently in use for generating time-resolved metabolomics data is given and contrasted with the needs of the discussed reverse engineering methods. The results of this assessment show that if full inference of a real-world metabolic network is the goal there is a large discrepancy between the requirements of reverse engineering of metabolic networks and contemporary measurement practice. Recommendations for improved time-resolved experimental designs are given.,
Molecular BioSystems
Erasmus MC: University Medical Center Rotterdam

Hendrickx, D., Hendriks, M., Eilers, P., Smilde, A., & Hoefsloot, H. (2011). Reverse engineering of metabolic networks, a critical assessment. Molecular BioSystems, 7(2), 511–520. doi:10.1039/c0mb00083c