An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Building a biologic model that describes the behavior of a cell in biologic systems is aimed at understanding the physiology of the cell, predicting the production of enzymes and metabolites, and providing a suitable data that is valid for bio-products. In addition, building a kinetic model requires...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020
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| Online Access: | https://umpir.ump.edu.my/id/eprint/29230/ |
| _version_ | 1848827272957526016 |
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| author | Mohammed Adam, Kunna Tuty Asmawaty, Abdul Kadir Muhammad Akmal, Remli Noorlin, Mohd Ali Kohbalan, Moorthy Noryanti, Muhammad |
| author_facet | Mohammed Adam, Kunna Tuty Asmawaty, Abdul Kadir Muhammad Akmal, Remli Noorlin, Mohd Ali Kohbalan, Moorthy Noryanti, Muhammad |
| author_sort | Mohammed Adam, Kunna |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Building a biologic model that describes the behavior of a cell in biologic systems is aimed at understanding the physiology of the cell, predicting the production of enzymes and metabolites, and providing a suitable data that is valid for bio-products. In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. As a result, kinetic parameters are mostly reported or estimated from different laboratories in different conditions and time consumption. Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. This method was proposed to increase the exploration and the exploitation of the Segment Particle Swarm Optimization algorithm (Se-PSO). The main metabolic model of E. coli was used as a benchmark which contained 172 kinetic parameters distributed in five pathways. Seven kinetic parameters were well estimated based on the distance minimization between the simulation and the experimental results. The results revealed that the proposed method had the ability to deal with kinetic parameters estimation in terms of time consumption and distance minimization. |
| first_indexed | 2025-11-15T03:58:05Z |
| format | Article |
| id | ump-29230 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:05Z |
| publishDate | 2020 |
| publisher | MDPI AG |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-292302025-09-26T04:19:47Z https://umpir.ump.edu.my/id/eprint/29230/ An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli Mohammed Adam, Kunna Tuty Asmawaty, Abdul Kadir Muhammad Akmal, Remli Noorlin, Mohd Ali Kohbalan, Moorthy Noryanti, Muhammad QA75 Electronic computers. Computer science Building a biologic model that describes the behavior of a cell in biologic systems is aimed at understanding the physiology of the cell, predicting the production of enzymes and metabolites, and providing a suitable data that is valid for bio-products. In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. As a result, kinetic parameters are mostly reported or estimated from different laboratories in different conditions and time consumption. Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. This method was proposed to increase the exploration and the exploitation of the Segment Particle Swarm Optimization algorithm (Se-PSO). The main metabolic model of E. coli was used as a benchmark which contained 172 kinetic parameters distributed in five pathways. Seven kinetic parameters were well estimated based on the distance minimization between the simulation and the experimental results. The results revealed that the proposed method had the ability to deal with kinetic parameters estimation in terms of time consumption and distance minimization. MDPI AG 2020 Article PeerReviewed pdf en cc_by_4 https://umpir.ump.edu.my/id/eprint/29230/1/6.%20An%20enhanced%20segment%20particle%20swarm%20optimization%20algorithm.pdf Mohammed Adam, Kunna and Tuty Asmawaty, Abdul Kadir and Muhammad Akmal, Remli and Noorlin, Mohd Ali and Kohbalan, Moorthy and Noryanti, Muhammad (2020) An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli. Processes, 8 (8). pp. 1-14. ISSN 2227-9717. (Published) https://doi.org/10.3390/pr8080963 https://doi.org/10.3390/pr8080963 https://doi.org/10.3390/pr8080963 |
| spellingShingle | QA75 Electronic computers. Computer science Mohammed Adam, Kunna Tuty Asmawaty, Abdul Kadir Muhammad Akmal, Remli Noorlin, Mohd Ali Kohbalan, Moorthy Noryanti, Muhammad An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title | An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title_full | An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title_fullStr | An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title_full_unstemmed | An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title_short | An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli |
| title_sort | enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of escherichia coli |
| topic | QA75 Electronic computers. Computer science |
| url | https://umpir.ump.edu.my/id/eprint/29230/ https://umpir.ump.edu.my/id/eprint/29230/ https://umpir.ump.edu.my/id/eprint/29230/ |