Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Carlos Pozo, Alberto Marín-Sanguino, Rui Alves, Gonzalo Guillén-Gosálbez, Laureano Jiménez, Albert Sorribas

Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization.