Ahmad Muhaimin, Ismail and Muhammad Akmal, Remli and Yee Wen, Choon and Nurul Athirah, Nasarudin and Norsyahidatul Nazirah, Ismail and Mohd Arfian, Ismail and Mohd Saberi, Mohamad (2023) Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway. Journal of integrative bioinformatics, 20 (2). pp. 1-8. ISSN 1613-4516. (Published)
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Abstract
Analyzing metabolic pathways in systems biology requires accurate kinetic parameters that represent the simulated in vivo processes. Simulation of the fermentation pathway in the Saccharomyces cerevisiae kinetic model help saves much time in the optimization process. Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. Parameter estimation is conducted to obtain the optimal values for parameters related to the fermentation process. This step is essential because insufficient identification of model parameters can cause erroneous conclusions. The kinetic parameters cannot be measured directly. Therefore, they must be estimated from the experimental data either in vitro or in vivo. Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae to obtain more accurate values. A metabolite with a total of six parameters is involved in this article. The experimental results show that ABC outperforms other estimation algorithms and gives more accurate kinetic parameter values for the simulated model. Most of the estimated kinetic parameter values obtained from the proposed algorithm are the closest to the experimental data.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Artificial bee colony algorithm; Artificial intelligence; Bioinformatics; Data science; Fermentation pathway; Parameter estimation |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 30 Aug 2023 08:16 |
| Last Modified: | 30 Aug 2023 08:16 |
| URI: | http://umpir.ump.edu.my/id/eprint/38359 |
| Download Statistic: | View Download Statistics |
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