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has been cited by the following article:

• TITLE: Optimization of the bioconversion of glycerol to ethanol using Escherichia coli by implementing a bi-level programming framework for proposing gene transcription control strategies based on genetic algorithms

  AUTHORS: Carol Milena Barreto-Rodriguez, Jessica Paola Ramirez-Angulo, Jorge Mario Gomez-Ramirez, Luke Achenie, Andres Fernando Gonzalez-Barrios

  KEYWORDS: Bi-level Optimization; Escherichia coli; Metabolic Flux Analysis; Genetic Algorithm

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.3 No.4, August 23, 2012

  ABSTRACT: In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approaches that can be exploited in order to enhance yield of processes which are based on biological reactions. Here, we propose an evolutionary approach aiming to suggest different mutant for augmenting ethanol yield using glycerol as substrate in Escherichia coli. We found that this algorithm, even though is far from providing the global optimum, is able to uncover genes that a global optimizer would be incapable of. By over-expressing accB, eno, dapE, and accA mutants in ethanol production was augmented up to 2 fold compared to its counterpart E. coli BW25113.