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Natural computation meta-heuristics for the in silico optimization of microbial strains

  • BMC Bioinformatics, 9(499), 2008

Publisher: Springer Nature

Abstract

Background: One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for in silico metabolic engineering, for example, to identify sets of ...

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ISI Web of Science® Citations: 42

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