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

Lookup NU author(s): James Skelton, Dr Jennifer Hallinan, Sunny Park, Professor Anil Wipat

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Abstract

© 2016 IEEE. 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.


Publication metadata

Author(s): Skelton DJ, Hallinan JS, Park S, Wipat A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: CIBCB 2016 - Annual IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology

Year of Conference: 2016

Online publication date: 02/01/2017

Acceptance date: 02/04/2016

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/CIBCB.2016.7758101

DOI: 10.1109/CIBCB.2016.7758101

Library holdings: Search Newcastle University Library for this item

ISBN: 9781467394727


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