Computational Tools for Strain Optimization by Tuning the Optimal Level of Gene Expression

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 154)

Abstract

In this work, a plug-in for the OptFlux Metabolic Engineering platform is presented, implementing methods that allow the identification of sets of genes to over/under express, relatively to their wild type levels. The optimization methods used are Simulated Annealing and Evolutionary Algorithms, working with a novel representation and operators. This overcomes the limitations of previous approaches based solely on gene knockouts, bringing new avenues for Biotechnology, fostering the discovery of genetic manipulations able to increase the production of certain compounds using a host microbe. The plug-in is made freely available together with appropriate documentation.

Keywords

Simulated Annealing Mutation Operator Gene Knockout Mixed Integer Linear Programming Flux Balance Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Emanuel Gonçalves
    • 1
  • Isabel Rocha
    • 2
  • Miguel Rocha
    • 1
  1. 1.CCTCUniversity of MinhoBragaPortugal
  2. 2.CEB / IBBUniversity of MinhoBragaPortugal

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