Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis

Many high-demand industrial products are generated by microorganisms, including fuels, food, vitamins, and other chemicals. Metabolic engineering is the method of circumventing cellular control to manufacture a desirable product or to create a new product that the host cells do not normally need to...

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Main Authors: Wan, Ting Leong, Mohd Saberi, Mohamad, Kohbalan, Moorthy, Yee, Wen Choon, Hasyiya Karimah, Adli, Khairul Nizar Syazwan, W. S. W, Loo, Keat Wei, Nazar, Zaki
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Published: IGI Global’s 2022
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Online Access:http://umpir.ump.edu.my/id/eprint/34977/
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author Wan, Ting Leong
Mohd Saberi, Mohamad
Kohbalan, Moorthy
Yee, Wen Choon
Hasyiya Karimah, Adli
Khairul Nizar Syazwan, W. S. W
Loo, Keat Wei
Nazar, Zaki
author_facet Wan, Ting Leong
Mohd Saberi, Mohamad
Kohbalan, Moorthy
Yee, Wen Choon
Hasyiya Karimah, Adli
Khairul Nizar Syazwan, W. S. W
Loo, Keat Wei
Nazar, Zaki
author_sort Wan, Ting Leong
building UMP Institutional Repository
collection Online Access
description Many high-demand industrial products are generated by microorganisms, including fuels, food, vitamins, and other chemicals. Metabolic engineering is the method of circumventing cellular control to manufacture a desirable product or to create a new product that the host cells do not normally need to produce. One of the objectives of microorganism metabolic engineering is to maximise the production of a desired product. However, owing to the structure of the regulatory cellular and metabolic network, identifying specific genes to be knocked out is difficult. The development of optimization algorithms often confronts issues such as easily trapping in local maxima and handling multivariate and multimodal functions inefficiently. To predict the gene knockout list that can generate high yields of desired product, a hybrid of firefly algorithm and dynamic flux balance analysis (FADFBA) is proposed. This paper focuses on the ethanol production of Escherichia coli (E. coli). The findings of the experiments include gene lists, ethanol production, growth rate, and the performance of FADFBA. , Universiti Teknologi Malaysia, Malaysia , United Arab Emirates University, UAE* Kohbalan Moorthy, Universiti Malaysia Pahang, Malaysia , Universiti Malaysia Kelantan, Malaysia , Universiti Malaysia Kelantan, Malaysia ., Universiti Malaysia Kelantan, Malaysia , Universiti Tunku Abdul Rahman, Malaysia , United Arab Emirate University, UAE
first_indexed 2025-11-15T03:16:28Z
format Article
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institution Universiti Malaysia Pahang
institution_category Local University
last_indexed 2025-11-15T03:16:28Z
publishDate 2022
publisher IGI Global’s
recordtype eprints
repository_type Digital Repository
spelling ump-349772022-08-26T08:22:22Z http://umpir.ump.edu.my/id/eprint/34977/ Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis Wan, Ting Leong Mohd Saberi, Mohamad Kohbalan, Moorthy Yee, Wen Choon Hasyiya Karimah, Adli Khairul Nizar Syazwan, W. S. W Loo, Keat Wei Nazar, Zaki Q Science (General) QA75 Electronic computers. Computer science Many high-demand industrial products are generated by microorganisms, including fuels, food, vitamins, and other chemicals. Metabolic engineering is the method of circumventing cellular control to manufacture a desirable product or to create a new product that the host cells do not normally need to produce. One of the objectives of microorganism metabolic engineering is to maximise the production of a desired product. However, owing to the structure of the regulatory cellular and metabolic network, identifying specific genes to be knocked out is difficult. The development of optimization algorithms often confronts issues such as easily trapping in local maxima and handling multivariate and multimodal functions inefficiently. To predict the gene knockout list that can generate high yields of desired product, a hybrid of firefly algorithm and dynamic flux balance analysis (FADFBA) is proposed. This paper focuses on the ethanol production of Escherichia coli (E. coli). The findings of the experiments include gene lists, ethanol production, growth rate, and the performance of FADFBA. , Universiti Teknologi Malaysia, Malaysia , United Arab Emirates University, UAE* Kohbalan Moorthy, Universiti Malaysia Pahang, Malaysia , Universiti Malaysia Kelantan, Malaysia , Universiti Malaysia Kelantan, Malaysia ., Universiti Malaysia Kelantan, Malaysia , Universiti Tunku Abdul Rahman, Malaysia , United Arab Emirate University, UAE IGI Global’s 2022 Article PeerReviewed Wan, Ting Leong and Mohd Saberi, Mohamad and Kohbalan, Moorthy and Yee, Wen Choon and Hasyiya Karimah, Adli and Khairul Nizar Syazwan, W. S. W and Loo, Keat Wei and Nazar, Zaki (2022) Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis. International Journal of Swarm Intelligence Research, 13 (1). pp. 1-13. ISSN 1947-9263. (Published) https://doi.org/10.4018/IJSIR.299845 10.4018/IJSIR
spellingShingle Q Science (General)
QA75 Electronic computers. Computer science
Wan, Ting Leong
Mohd Saberi, Mohamad
Kohbalan, Moorthy
Yee, Wen Choon
Hasyiya Karimah, Adli
Khairul Nizar Syazwan, W. S. W
Loo, Keat Wei
Nazar, Zaki
Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title_full Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title_fullStr Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title_full_unstemmed Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title_short Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis
title_sort enhancement of ethanol production using a hybrid of firefly algorithm and dynamic flux balance analysis
topic Q Science (General)
QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/34977/
http://umpir.ump.edu.my/id/eprint/34977/
http://umpir.ump.edu.my/id/eprint/34977/