We present a cybernetic perspective of metabolic systems, designed to take full account of regulatory processes, which profoundly influence the course of metabolism through dependence not only on the organism's genomic constitution, but also on abiotic environmental influences. The cybernetic perspective relies on proposing "mechanisms" of choice behavior by which biological systems drive enzyme syntheses and allosteric processes for chemical reactions that promote perceived local or global cellular objectives. This article is an exposition of the framework, attempting to show how experimental data can be used to facilitate model identification. Such an approach is proposed with the view to exploit detailed cellular measurements such as metabolite and mRNA or enzyme levels. We present a modular approach that originates with the metabolic network to be modeled and systematically breaks it down into smaller regulatory units which can be modeled using previously established cybernetic competitions [Kompala, D. S., Ramkrishna, D., Jansen, N. B., W Tsao, G. T. (1986). Investigation of bacterial growth on mixed substrates: experimental evaluation of cybernetic models. Biotechnology and Bioengineering, 28, 1044-1055; Straight, J. V., W Ramkrishna, D. (1990). Regulation of complex growth dynamics-substitutable and complementary processes. Abstracts of the papers of The American Chemical Society, 200, 4-BIOT]. Experimental data can assist in rapid formulation of numerous specific combinatorial alternatives suggested by the metabolic network. Methods are discussed within this continuously evolving framework for the identification of cybernetic models from data with illustrative examples. (c) 2004 Published by Elsevier Ltd.