Muhammad Azharuddin, Arif and Mohd Saberi, Mohamad and Muhammad Shafie, Abd Latif and Safaai, Deris and Muhammad Akmal, Remli and Kauthar, Mohd Daud and Zuwairie, Ibrahim and Omatu, Sigeru and Corchado, Juan Manuel (2018) A hybrid of Cuckoo Search and Minimization of Metabolic Adjustment to optimize metabolites production in genome-scale models. Computers in Biology and Medicine, 102. pp. 112-119. ISSN 0010-4825. (Published)
|
Pdf
A hybrid of Cuckoo Search and Minimization of Metabolic Adjustment to optimize metabolites production in genome.pdf Download (278kB) | Preview |
Abstract
Metabolic engineering involves the modification and alteration of metabolic pathways to improve the production of desired substance. The modification can be made using in silicogene knockout simulation that is able to predict and analyse the disrupted genes which may enhance the metabolites production. Global optimization algorithms have been widely used for identifying gene knockout strategies. However, their productions were less than theoretical maximum and the algorithms are easily trapped into local optima. These algorithms also require a very large computation time to obtain acceptable results. This is due to the complexity of the metabolic models which are high dimensional and contain thousands of reactions. In this paper, a hybrid algorithm of Cuckoo Search and Minimization of Metabolic Adjustment is proposed to overcome the aforementioned problems. The hybrid algorithm searches for the near-optimal set of gene knockouts that leads to the overproduction of metabolites. Computational experiments on two sets of genome-scale metabolic models demonstrate that the proposed algorithm is better than the previous works in terms of growth rate, Biomass Product Couple Yield, and computation time.
| Item Type: | Article |
|---|---|
| Additional Information: | Index by Scopus |
| Uncontrolled Keywords: | Artificial intelligence; Bioinformatics; Metabolic engineering; Cuckoo Search; Minimization of Metabolic Adjustment; Gene knockout |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Computer System And Software Engineering Faculty of Electrical & Electronic Engineering |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 15 Nov 2018 03:39 |
| Last Modified: | 15 Nov 2018 03:39 |
| URI: | http://umpir.ump.edu.my/id/eprint/22302 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |