Evolutionary Algorithms for Parameter Estimation of Metabolic Systems

Abstract

For many years, computational tools have been widely applied to study such complex systems as metabolic networks. One of the principal questions in modeling of metabolic systems is the parameter estimation of model, which is related to a nonlinear programming problem. Two types of evolutionary algorithms, Differential Evolution and Self-Organizing Migrating Algorithm, are applied to the well-studied metabolic system, the urea cycle of the mammalian hepatocyte. The algorithms provide an effective approach in parameters identification of the model. © Springer International Publishing Switzerland 2013.