Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway

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

doi:10.1109/CIBCB.2016.7758101

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 proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

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 language	English
Title of host publication	2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Subtitle of host publication	proceedings
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
ISBN (Print)	9781467394727
DOIs	https://doi.org/10.1109/CIBCB.2016.7758101
Publication status	Published - 2016
Event	The annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2016) - Chiang Mai, Thailand Duration: 5 Oct 2016 → 7 Oct 2016

Conference

Conference	The annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2016)
City	Chiang Mai, Thailand
Period	5/10/16 → 7/10/16

Keywords

evolutionary computation
data integration
metabolic engineering
genomics
synthetic biology
Evolutionary computation

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10.1109/CIBCB.2016.7758101

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Hallinan, J. S., Skelton, D. J., Park, S., & Wipat, A. (2016). Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway. In 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB): proceedings (pp. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CIBCB.2016.7758101

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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.",

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Hallinan, JS, Skelton, DJ, Park, S & Wipat, A 2016, Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway. in 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB): proceedings. Institute of Electrical and Electronics Engineers, Piscataway, NJ, pp. 1-6, The annual IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (2016), Chiang Mai, Thailand, 5/10/16. https://doi.org/10.1109/CIBCB.2016.7758101

Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway. / Hallinan, J. S.; Skelton, D. J.; Park, S. et al.
2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB): proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2016. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AB - 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.

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KW - data integration

KW - metabolic engineering

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Hallinan JS, Skelton DJ, Park S, Wipat A. Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway. In 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB): proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers. 2016. p. 1-6 doi: 10.1109/CIBCB.2016.7758101

Computational intelligence for metabolic pathway design: application to the pentose phosphate pathway

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