An Iterative Strategy for Yield Optimization of Metabolic Pathways

摘要

This paper addresses product yield optimization of metabolic pathways represented by the generalized mass action (GMA) systems. In most cases nonconvex yield optimization problems with GMA models cannot be transformed into convex optimization problems through geometric programming, but an iterative strategy can be used to compute the optimal solution by solving a series of geometric programming. The presented iterative strategy is applied to the fermentation pathway in Saccharomyces cerevisiae and shown to the effectiveness of the method.