In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment
Microorganisms commonly produce many high-demand industrial products like fuels, food, vitamins, and other chemicals. Microbial strains are the strains of microorganisms, which can be optimized to improve their technological properties through metabolic engineering. Metabolic engineering is the proc...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2021-08-01
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| Series: | Journal of Integrative Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jib-2020-0037 |
| _version_ | 1828733926123765760 |
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| author | Man Mei Yen Mohamad Mohd Saberi Choon Yee Wen Ismail Mohd Arfian |
| author_facet | Man Mei Yen Mohamad Mohd Saberi Choon Yee Wen Ismail Mohd Arfian |
| author_sort | Man Mei Yen |
| collection | DOAJ |
| description | Microorganisms commonly produce many high-demand industrial products like fuels, food, vitamins, and other chemicals. Microbial strains are the strains of microorganisms, which can be optimized to improve their technological properties through metabolic engineering. Metabolic engineering is the process of overcoming cellular regulation in order to achieve a desired product or to generate a new product that the host cells do not usually need to produce. The prediction of genetic manipulations such as gene knockout is part of metabolic engineering. Gene knockout can be used to optimize the microbial strains, such as to maximize the production rate of chemicals of interest. Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in Escherichia coli (E. coli). |
| first_indexed | 2024-04-12T22:39:17Z |
| format | Article |
| id | doaj.art-5f109bac1b6749de9e046e8e9899ac0a |
| institution | Directory Open Access Journal |
| issn | 1613-4516 |
| language | English |
| last_indexed | 2024-04-12T22:39:17Z |
| publishDate | 2021-08-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Integrative Bioinformatics |
| spelling | doaj.art-5f109bac1b6749de9e046e8e9899ac0a2022-12-22T03:13:46ZengDe GruyterJournal of Integrative Bioinformatics1613-45162021-08-01183331710.1515/jib-2020-0037In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustmentMan Mei Yen0Mohamad Mohd Saberi1Choon Yee Wen2Ismail Mohd Arfian3School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor, MalaysiaDepartment of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain17666, Abu Dhabi, United Arab EmiratesInstitute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, Kota Bharu 16100, Kelantan, Malaysia; and Department of Data Science, Universiti Malaysia Kelantan, Kota Bharu 16100, Kelantan, MalaysiaFaculty of Computing (FKOM), College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang, MalaysiaMicroorganisms commonly produce many high-demand industrial products like fuels, food, vitamins, and other chemicals. Microbial strains are the strains of microorganisms, which can be optimized to improve their technological properties through metabolic engineering. Metabolic engineering is the process of overcoming cellular regulation in order to achieve a desired product or to generate a new product that the host cells do not usually need to produce. The prediction of genetic manipulations such as gene knockout is part of metabolic engineering. Gene knockout can be used to optimize the microbial strains, such as to maximize the production rate of chemicals of interest. Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in Escherichia coli (E. coli).https://doi.org/10.1515/jib-2020-0037bat algorithmbioinformaticsescherichia coligene knockoutlactateminimization of metabolic adjustmentsuccinate |
| spellingShingle | Man Mei Yen Mohamad Mohd Saberi Choon Yee Wen Ismail Mohd Arfian In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment Journal of Integrative Bioinformatics bat algorithm bioinformatics escherichia coli gene knockout lactate minimization of metabolic adjustment succinate |
| title | In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment |
| title_full | In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment |
| title_fullStr | In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment |
| title_full_unstemmed | In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment |
| title_short | In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment |
| title_sort | in silico gene knockout prediction using a hybrid of bat algorithm and minimization of metabolic adjustment |
| topic | bat algorithm bioinformatics escherichia coli gene knockout lactate minimization of metabolic adjustment succinate |
| url | https://doi.org/10.1515/jib-2020-0037 |
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