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A hybrid of cuckoo search and minimization of metabolic adjustment to optimize metabolites production in genome-scale models

Arif, Muhammad Azharuddin and Mohamad, Mohd. Saberi and Abd. Latif, Muhammad Shafie and Deris, Safaai and Remli, Muhammad Akmal and Mohd. Daud, Kauthar and Ibrahim, Zuwairie 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

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Official URL: http://dx.doi.org/10.1016/j.compbiomed.2018.09.015

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 silico gene 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
Uncontrolled Keywords:artificial intelligence, bioinformatics, cuckoo search, gene knockout, metabolic engineering
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:84421
Deposited By: Yanti Mohd Shah
Deposited On:11 Jan 2020 15:07
Last Modified:11 Jan 2020 15:07

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