Mei, Kie Hon and Mohd Saberi, Mohamad and Abdul Hakim, Mohamed Salleh and Yee, Wen Choon and Kauthar, Mohd Daud and Muhammad Akmal, Remli and Mohd Arfian, Ismail and Omatu, Sigeru and Sinnott, Richard O. and Corchado, Juan Manuel (2019) Identifying a Gene Knockout Strategy Using a Hybrid of Simple Constrained Artificial Bee Colony Algorithm and Flux Balance Analysis to Enhance the Production of Succinate and Lactate in Escherichia Coli. Interdisciplinary Sciences: Computational Life Sciences, 11 (1). pp. 33-44. ISSN 1913-2751. (Published)
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Abstract
In recent years, metabolic engineering has gained central attention in numerous fields of science because of its capability to manipulate metabolic pathways in enhancing the expression of target phenotypes. Due to this, many computational approaches that perform genetic manipulation have been developed in the computational biology field. In metabolic engineering, conventional methods have been utilized to upgrade the generation of lactate and succinate in E. coli, although the yields produced are usually way below their theoretical maxima. To overcome the drawbacks of such conventional methods, development of hybrid algorithm is introduced to obtain an optimal solution by proposing a gene knockout strategy in E. coli which is able to improve the production of lactate and succinate. The objective function of the hybrid algorithm is optimized using a swarm intelligence optimization algorithm and a Simple Constrained Artificial Bee Colony (SCABC) algorithm. The results maximize the production of lactate and succinate by resembling the gene knockout in E. coli. The Flux Balance Analysis (FBA) is integrated in a hybrid algorithm to evaluate the growth rate of E. coli as well as the productions of lactate and succinate. This results in the identification of a gene knockout list that contributes to maximizing the production of lactate and succinate in E. coli.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Gene Knockout Strategies; Escherichia Coli; Lactate; Succinate; Simple Constrained Artificial Bee Colony; Flux Balance Analysis |
| Subjects: | Q Science > Q Science (General) |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Noorul Farina Arifin |
| Date Deposited: | 10 May 2019 06:33 |
| Last Modified: | 10 May 2019 06:33 |
| URI: | http://umpir.ump.edu.my/id/eprint/24904 |
| Download Statistic: | View Download Statistics |
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