Lee, M. K. and Mohd Saberi, Mohamad and Choon, Yee Wen and Kauthar, Mohd Daud and Nurul Athirah, Nasarudin and Mohd Arfian, Ismail and Zuwairie, Ibrahim and Suhaimi, Napis and Sinnott, Richard O. (2020) Comparison of optimization-modelling methods for metabolites production in escherichia coli. Journal of integrative bioinformatics, 17 (1). pp. 1-7. ISSN 1613-4516. (Published)
|
Pdf (Open access)
Comparison of optimization-modelling methods for metabolites production.pdf Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (110kB) | Preview |
Abstract
The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite’s production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Metaheuristic algorithms; Minimization of metabolic adjustment; Metabolic engineering; Bioinformatics; Artificial intelligence |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computer System And Software Engineering Faculty of Manufacturing Engineering |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 30 Jun 2021 14:31 |
| Last Modified: | 30 Jun 2021 14:31 |
| URI: | http://umpir.ump.edu.my/id/eprint/31042 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |