Advancement of genomic research and anal. techniques enables an in-depth understanding of individual components in the cellular metab. The crit. subject is the integration of massive exptl. details and the quantification of the contributions of individual genes and their product enzymes in controlling and regulating the metabolic network. We have recently developed a math. and computational framework that utilizes the metabolic control anal. framework and takes into account the uncertainty in the exptl. information. Large-scale sampling procedure is performed to simulate the variant exptl. data and statistical anal. is exploited. The framework is applied on the compartmentalized central metab. of Saccharomyces cerevisiae under different growth cultivations. Essential properties of the network are discovered including the primary controlling enzymes of the metabolic network, the role of energy supply and demand in regulating metabolic rates, and the physiol. clustering of the responses of the metabolic fluxes to genetic and environmental changes. We discuss how these results lead to the interpretation of exptl. observations and provide guidance for the design of metabolic engineering projects. [on SciFinder (R)]