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Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment


Citation

Tang, Phooi Wah and Choon, Yee Wen and Mohamad, Mohd Saberi and Deris, Safaai and Napis, Suhaimi (2015) Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment. Journal of Bioscience and Bioengineering, 119 (3). pp. 363-368. ISSN 1389-1723; ESSN: 1347-4421

Abstract

Metabolic engineering is a research field that focuses on the design of models for metabolism, and uses computational procedures to suggest genetic manipulation. It aims to improve the yield of particular chemical or biochemical products. Several traditional metabolic engineering methods are commonly used to increase the production of a desired target, but the products are always far below their theoretical maximums. Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. The dataset used in this work was from the iJO1366 Escherichia coli metabolic network. The experimental results include the production rate, growth rate and a list of knockout genes. From the comparative analysis, ABCMOMA produced better results compared to previous works, showing potential for solving genetic engineering problems.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Biotechnology and Biomolecular Sciences
DOI Number: https://doi.org/10.1016/j.jbiosc.2014.08.004
Publisher: Society for Biotechnology
Keywords: Artificial bee colony; Minimisation of metabolic adjustment; Gene knockout; Metabolic engineering; Escherichia coli
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 22 Dec 2015 08:55
Last Modified: 22 Dec 2015 08:55
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.jbiosc.2014.08.004
URI: http://psasir.upm.edu.my/id/eprint/34762
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