A Hybrid of Harmony Search and Minimization of Metabolic Adjustment for Optimization of Succinic Acid Production

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Nor Syahirah, Abdul Wahid and Mohd Saberi, Mohamad and Abdul Hakim, Mohamed Salleh and Safaai, Deris and Chan, Weng Howe and Omatu, Sigeru and Corchado, Juan Manuel and Muhammad Farhan, Sjaugi and Zuwairie, Ibrahim and Zulkifli, Md. Yusof (2016) A Hybrid of Harmony Search and Minimization of Metabolic Adjustment for Optimization of Succinic Acid Production. In: 10th International Conference on Practical Applications of Computational Biology & Bioinformatics. Advances in Intelligent Systems and Computing, 477 (Pt. IV). Springer, Switzerland, pp. 183-191. ISBN 978-3-319-40125-6 (print); 978-3-319-40126-3 (online)

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Official URL: http://dx.doi.org/10.1007/978-3-319-40126-3_19

Abstract

Succinic acid has been favored by researchers due to its industrial multi-uses. However, the production of succinic acid is far below cell theoretical maximum. The goal of this research is to identify the optimal set of gene knockouts for obtaining high production of succinic acid in microorganisms. Gene knockout is a widely used genetic engineering technique. Hence, a hybrid of Harmony Search (HS) and Minimization of Metabolic Adjustment (MOMA) is proposed. The dataset applied is a core Escherichia coli metabolic network model. Harmony Search is a meta-heuristic algorithm inspired by musicians’ improvisation process. Minimization of Metabolic Adjustment is used to calculate fitness closest to the wild-type, after mutant gene knockout. The result obtained from the proposed hybrid technique are knockout genes list and production rate after the deletion. This proposed technique is possible to be applied in wet laboratory experiment to increase the production of succinic acid in E. coli.

Item Type:Book Section
Uncontrolled Keywords:Bioinformatics; Artificial intelligence; Metabolic engineering; Harmony Search; Minimization of Metabolic Adjustment; Gene knockout
Subjects:Q Science > QH Natural history > QH426 Genetics
T Technology > TJ Mechanical engineering and machinery
Divisions:Faculty of Electrical & Electronic Engineering
Faculty of Manufacturing Engineering
ID Code:6822
Deposited By: Ms. Hazima Anuar
Deposited On:17 Jun 2016 10:14
Last Modified:30 Oct 2017 10:22

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