Computational intelligence for metabolic pathway design

application to the pentose phosphate pathway

J. S. Hallinan, D. J. Skelton, S. Park, A. Wipat

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Metabolic engineering is increasingly being used for the production of industrial products such as pharmaceuticals and enzymes. These chemicals have traditionally been chemically synthesized, but the application of synthetic biology techniques to microbes facilitates faster, cheaper production. Modelling and the integration of existing data can help inform the design of synthetic pathways. We applied an evolutionary algorithm to a flux balance model of metabolism in the industrially important bacterium Bacillus subtilis. Our target metabolites are sedoheptulose-7-phosphate and riboflavin, components of the pentose phosphate pathway. The algorithm combines the results of the flux balance analysis with phylogenetic information derived from data warehouses, to predict several potential interventions to the metabolic network, mostly involving knockouts of genes related to the pathway.
Original languageEnglish
Title of host publication2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Subtitle of host publicationproceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Print)9781467394727
DOIs
Publication statusPublished - 2016
EventThe annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2016) - Chiang Mai, Thailand
Duration: 5 Oct 20167 Oct 2016

Conference

ConferenceThe annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2016)
CityChiang Mai, Thailand
Period5/10/167/10/16

Keywords

  • evolutionary computation
  • data integration
  • metabolic engineering
  • genomics
  • synthetic biology
  • Evolutionary computation

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