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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.

The advances in genome sequencing and metabolic engineering have allowed the reengineering of the cellular function of an organism. Furthermore, given the abundance of omics data, data collection has increased considerably, thus shifting the perspective of molecular biology. Therefore, researchers h...

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Main Authors: Mohd. Daud, Kauthar, Ananda, Ridho, Zainudin, Suhaila, Howe, Chan Weng, Moorthy, Kohbalan, Md. Saleh, Nurul Izrin
Format: Article
Language:English
Published: Science and Information Organization 2023
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utm.my/105422/1/ChanWengHowe2023_OptimizingtheProductionofValuableMetabolites.pdf
http://eprints.utm.my/105422/
http://dx.doi.org/10.14569/IJACSA.2023.01410115
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spelling my.utm.1054222024-04-24T06:53:12Z http://eprints.utm.my/105422/ Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review. Mohd. Daud, Kauthar Ananda, Ridho Zainudin, Suhaila Howe, Chan Weng Moorthy, Kohbalan Md. Saleh, Nurul Izrin T Technology (General) TA Engineering (General). Civil engineering (General) The advances in genome sequencing and metabolic engineering have allowed the reengineering of the cellular function of an organism. Furthermore, given the abundance of omics data, data collection has increased considerably, thus shifting the perspective of molecular biology. Therefore, researchers have recently used artificial intelligence and machine learning tools to simulate and improve the reconstruction and analysis by identifying meaningful features from the large multi-omics dataset. This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. The research articles published between 2020 and 2023 on machine learning and constraintbased modeling have been collected, synthesized, and analyzed. The articles are obtained from the Web of Science and Scopus databases using the keywords: “Machine learning”, “flux balance analysis”, and “metabolic engineering”. At the end of the search, this review contained 13 records. This review paper aims to provide current trends and approaches in in silico metabolic engineering while providing research directions by highlighting the research gaps. In addition, we have discussed the methodology for integrating machine learning and constraint-based modeling approaches. Science and Information Organization 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/105422/1/ChanWengHowe2023_OptimizingtheProductionofValuableMetabolites.pdf Mohd. Daud, Kauthar and Ananda, Ridho and Zainudin, Suhaila and Howe, Chan Weng and Moorthy, Kohbalan and Md. Saleh, Nurul Izrin (2023) Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review. International Journal Of Advanced Computer Science And Applications, 14 (10). pp. 1091-1105. ISSN 2158-107X http://dx.doi.org/10.14569/IJACSA.2023.01410115 DOI: 10.14569/IJACSA.2023.01410115
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
Mohd. Daud, Kauthar
Ananda, Ridho
Zainudin, Suhaila
Howe, Chan Weng
Moorthy, Kohbalan
Md. Saleh, Nurul Izrin
Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
description The advances in genome sequencing and metabolic engineering have allowed the reengineering of the cellular function of an organism. Furthermore, given the abundance of omics data, data collection has increased considerably, thus shifting the perspective of molecular biology. Therefore, researchers have recently used artificial intelligence and machine learning tools to simulate and improve the reconstruction and analysis by identifying meaningful features from the large multi-omics dataset. This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. The research articles published between 2020 and 2023 on machine learning and constraintbased modeling have been collected, synthesized, and analyzed. The articles are obtained from the Web of Science and Scopus databases using the keywords: “Machine learning”, “flux balance analysis”, and “metabolic engineering”. At the end of the search, this review contained 13 records. This review paper aims to provide current trends and approaches in in silico metabolic engineering while providing research directions by highlighting the research gaps. In addition, we have discussed the methodology for integrating machine learning and constraint-based modeling approaches.
format Article
author Mohd. Daud, Kauthar
Ananda, Ridho
Zainudin, Suhaila
Howe, Chan Weng
Moorthy, Kohbalan
Md. Saleh, Nurul Izrin
author_facet Mohd. Daud, Kauthar
Ananda, Ridho
Zainudin, Suhaila
Howe, Chan Weng
Moorthy, Kohbalan
Md. Saleh, Nurul Izrin
author_sort Mohd. Daud, Kauthar
title Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
title_short Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
title_full Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
title_fullStr Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
title_full_unstemmed Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
title_sort optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms: a review.
publisher Science and Information Organization
publishDate 2023
url http://eprints.utm.my/105422/1/ChanWengHowe2023_OptimizingtheProductionofValuableMetabolites.pdf
http://eprints.utm.my/105422/
http://dx.doi.org/10.14569/IJACSA.2023.01410115
_version_ 1797906021717377024
score 13.211869

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