Many attempts to engineer cellular metab. have failed due to the complexity of cellular functions. Math. and computational methods are needed that can organize the available exptl. information, and provide insight and guidance for successful metabolic engineering. Two such methods are reviewed here. Both methods employ a (log)linear kinetic model of metab. that is constructed based on enzyme kinetics characteristics. The first method allows the description of the dynamic responses of metabolic systems subject to spatiotemporal variations in their parameters. The second method considers the product-oriented, constrained optimization of metabolic reaction networks using mixed-integer linear programming methods. The optimization framework is used in order to identify the combinations of the metabolic characteristics of the glycolytic enzymes from yeast and bacteria that will maximize ethanol prodn. The methods are also applied to the design of microbial ethanol prodn. metab. The results of the calcns. are in qual. agreement with the exptl. data presented. Expts. and calcns. suggest that, in resting Escherichia coli cells, ethanol prodn. and glucose uptake rates can be increased by 30 and 20%, resp., by overexpression of a deregulated pyruvate kinase, while increase in phosphofructokinase expression levels has no effect on ethanol prodn. and glucose uptake rates. [on SciFinder (R)]