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Department of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, USA.
Genome-scale metabolic models have a promising ability to describe cellular phenotypes accurately. Here we show that strains of Escherichia coli carrying a deletion of a single metabolic gene increase their growth rates (by 87% on average) during adaptive evolution and that the endpoint growth rates can be predicted computationally in 39 of 50 (78%) strains tested. These results show that computational models can be used to predict the eventual effects of genetic modifications.
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