Abstract
Abstract Genotype-phenotype relationship is fundamental to biology, and predicting different phenotypes based on the sequenced genome is one of the main goals for genome-scale metabolic model development. Phenotype phase plane (PhPP) analysis is a powerful tool to provide a global perspective on the genotype-phenotype relationship, and to help characterize different metabolic phenotypes. However, the traditional PhPP analysis is based on shadow price analysis, which provides limited information to characterize different phenotypes. In this work, we propose a system identification (SID) enhanced PhPP, which not only obtains information that could be obtained through shadow price analysis, but also provides additional information that helps characterize different phenotypes. The effectiveness of the SID-PhPP approach is demonstrated using an illustrative cell model and a core metabolic network model of E. coli.
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