Mohammed Adam Kunna, Azrag and Jasni Mohamad, Zain and Tuty Asmawaty, Abdul Kadir and Marina, Yusoff and Jaber, Aqeel Sakhy and Abdlrhman, Hybat Salih Mohamed and Ahmed, Yasmeen Hafiz Zaki and Husain, Mohamed Saad Bala (2023) Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso. Processes, 11 (126). pp. 1-25. ISSN 2227-9717. (Published)
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Abstract
The ability to create “structured models” of biological simulations is becoming more and more commonplace. Although computer simulations can be used to estimate the model, they are restricted by the lack of experimentally available parameter values, which must be approximated. In this study, an Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm that can estimate the values of small-scale kinetic parameters is described and applied to E. coli’s main metabolic network as a model system. The glycolysis, phosphotransferase system, pentose phosphate, the TCA cycle, gluconeogenesis, glyoxylate pathways, and acetate formation pathways of Escherichia coli are represented by the Differential Algebraic Equations (DAE) system for the metabolic network. However, this algorithm uses segments to organize particle movements and the dynamic inertia weight ((Formula presented.)) to increase the algorithm’s exploration and exploitation potential. As an alternative to the state-of-the-art algorithm, this adjustment improves estimation accuracy. The numerical findings indicate a good agreement between the observed and predicted data. In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. As a result of this innovative approach, it was concluded that small-scale and even entire cell kinetic model parameters can be developed.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Algorithm; E. coli; Estimation; Kinetic parameters; Simulation |
| Subjects: | Q Science > QD Chemistry T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TP Chemical technology |
| Faculty/Division: | Institute of Postgraduate Studies College of Engineering Faculty of Chemical and Process Engineering Technology |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 05 Sep 2023 03:49 |
| Last Modified: | 05 Sep 2023 03:49 |
| URI: | http://umpir.ump.edu.my/id/eprint/38223 |
| Download Statistic: | View Download Statistics |
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