Reverse engineering of metabolic networks, a critical assessment

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.


D.M. Hendrickx, M.M.W.B. Hendriks, P.H.C. Eilers, A.K. Smilde, H.C.J. Hoefsloot
2011; 7 (2): 511-520
Published in: 
Molecular Biosystems
Date of publication: 
February, 2011
Status of the publication: