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Computational modeling in metabolic engineering involves the prediction of genetic manipulations that would lead to optimized microbial strains, maximizing the production rate of chemicals of interest. Various computational methods are based on constraint-based modeling, which enables to anticipate the effect of genetic manipulations on cellular metabolism considering a genome-scale metabolic network. However, current methods do not account for the presence of competing pathways in a metabolic network that may diverge metabolic flux away from producing a required chemical, resulting in lower (or even zero) chemical production rates in reality-making these methods somewhat over optimistic.

Predicting metabolic engineering knockout strategies for chemical production: accounting for competing pathways