A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana
Recently, modelling and simulation have been used and applied to understand biological systems better. Therefore, the development of precise computational models of a biological system is essential. This model is a mathematical expression derived from a series of parameters of the system. The measur...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020
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| Online Access: | http://umpir.ump.edu.my/id/eprint/28977/1/A%20Hybrid%20of%20Particle%20Swarm%20Optimization%20and%20Harmony.pdf |
| _version_ | 1825813447687798784 |
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| author | Mohamad Saufie, Rosle Mohd Saberi, Mohamad Yee, Wen Choon Zuwairie, Ibrahim González-Briones, Alfonso Chamoso, Pablo Corchado, Juan Manuel |
| author_facet | Mohamad Saufie, Rosle Mohd Saberi, Mohamad Yee, Wen Choon Zuwairie, Ibrahim González-Briones, Alfonso Chamoso, Pablo Corchado, Juan Manuel |
| author_sort | Mohamad Saufie, Rosle |
| collection | UMP |
| description | Recently, modelling and simulation have been used and applied to understand biological systems better. Therefore, the development of precise computational models of a biological system is essential. This model is a mathematical expression derived from a series of parameters of the system. The measurement of parameter values through experimentation is often expensive and time-consuming. However, if a simulation is used, the manipulation of computational parameters is easy, and thus the behaviour of a biological system model can be altered for a better understanding. The complexity and nonlinearity of a biological system make parameter estimation the most challenging task in modelling. Therefore, this paper proposes a hybrid of Particle Swarm Optimization (PSO) and Harmony Search (HS), also known as PSOHS, designated to determine the kinetic parameter values of essential amino acids, mainly aspartate metabolism, in Arabidopsis thaliana. Three performance measurements are used in this paper to evaluate the proposed PSOHS: the standard deviation, nonlinear least squared error, and computational time. The proposed algorithm outperformed the other two methods, namely Simulated Annealing and the downhill simplex method, and proved that PSOHS is a more suitable algorithm for estimating kinetic parameter values. |
| first_indexed | 2024-03-06T12:44:09Z |
| format | Article |
| id | UMPir28977 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:44:09Z |
| publishDate | 2020 |
| publisher | MDPI AG |
| record_format | dspace |
| spelling | UMPir289772020-08-07T03:52:28Z http://umpir.ump.edu.my/id/eprint/28977/ A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana Mohamad Saufie, Rosle Mohd Saberi, Mohamad Yee, Wen Choon Zuwairie, Ibrahim González-Briones, Alfonso Chamoso, Pablo Corchado, Juan Manuel Q Science (General) Recently, modelling and simulation have been used and applied to understand biological systems better. Therefore, the development of precise computational models of a biological system is essential. This model is a mathematical expression derived from a series of parameters of the system. The measurement of parameter values through experimentation is often expensive and time-consuming. However, if a simulation is used, the manipulation of computational parameters is easy, and thus the behaviour of a biological system model can be altered for a better understanding. The complexity and nonlinearity of a biological system make parameter estimation the most challenging task in modelling. Therefore, this paper proposes a hybrid of Particle Swarm Optimization (PSO) and Harmony Search (HS), also known as PSOHS, designated to determine the kinetic parameter values of essential amino acids, mainly aspartate metabolism, in Arabidopsis thaliana. Three performance measurements are used in this paper to evaluate the proposed PSOHS: the standard deviation, nonlinear least squared error, and computational time. The proposed algorithm outperformed the other two methods, namely Simulated Annealing and the downhill simplex method, and proved that PSOHS is a more suitable algorithm for estimating kinetic parameter values. MDPI AG 2020 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/28977/1/A%20Hybrid%20of%20Particle%20Swarm%20Optimization%20and%20Harmony.pdf Mohamad Saufie, Rosle and Mohd Saberi, Mohamad and Yee, Wen Choon and Zuwairie, Ibrahim and González-Briones, Alfonso and Chamoso, Pablo and Corchado, Juan Manuel (2020) A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana. Processes, 8 (921). pp. 1-12. ISSN 2227-9717. (Published) https://doi.org/10.3390/pr8080921 https://doi.org/10.3390/pr8080921 |
| spellingShingle | Q Science (General) Mohamad Saufie, Rosle Mohd Saberi, Mohamad Yee, Wen Choon Zuwairie, Ibrahim González-Briones, Alfonso Chamoso, Pablo Corchado, Juan Manuel A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title | A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title_full | A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title_fullStr | A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title_full_unstemmed | A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title_short | A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana |
| title_sort | hybrid of particle swarm optimization and harmony search to estimate kinetic parameters in arabidopsis thaliana |
| topic | Q Science (General) |
| url | http://umpir.ump.edu.my/id/eprint/28977/1/A%20Hybrid%20of%20Particle%20Swarm%20Optimization%20and%20Harmony.pdf |
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