Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis
The Sel’kov model for glycolysis is a highly effective tool in capturing the complex feedback mechanisms that occur within a biochemical system. However, accurately predicting the behavior of this system is challenging due to its nonlinearity, stiffness, and parameter sensitivity. In this paper, we...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/14/3216 |
| _version_ | 1797588462991310848 |
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| author | Jamshaid Ul Rahman Sana Danish Dianchen Lu |
| author_facet | Jamshaid Ul Rahman Sana Danish Dianchen Lu |
| author_sort | Jamshaid Ul Rahman |
| collection | DOAJ |
| description | The Sel’kov model for glycolysis is a highly effective tool in capturing the complex feedback mechanisms that occur within a biochemical system. However, accurately predicting the behavior of this system is challenging due to its nonlinearity, stiffness, and parameter sensitivity. In this paper, we present a novel deep neural network-based method to simulate the Sel’kov glycolysis model of ADP and F6P, which overcomes the limitations of conventional numerical methods. Our comprehensive results demonstrate that the proposed approach outperforms traditional methods and offers greater reliability for nonlinear dynamics. By adopting this flexible and robust technique, researchers can gain deeper insights into the complex interactions that drive biochemical systems. |
| first_indexed | 2024-03-11T00:52:25Z |
| format | Article |
| id | doaj.art-fd4ea77059a6443a932a9aa7767d0468 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T00:52:25Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-fd4ea77059a6443a932a9aa7767d04682023-11-18T20:22:19ZengMDPI AGMathematics2227-73902023-07-011114321610.3390/math11143216Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive AnalysisJamshaid Ul Rahman0Sana Danish1Dianchen Lu2School of Mathematical Sciences, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, ChinaAbdus Salam School of Mathematical Sciences, GC University, Lahore 54600, PakistanSchool of Mathematical Sciences, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, ChinaThe Sel’kov model for glycolysis is a highly effective tool in capturing the complex feedback mechanisms that occur within a biochemical system. However, accurately predicting the behavior of this system is challenging due to its nonlinearity, stiffness, and parameter sensitivity. In this paper, we present a novel deep neural network-based method to simulate the Sel’kov glycolysis model of ADP and F6P, which overcomes the limitations of conventional numerical methods. Our comprehensive results demonstrate that the proposed approach outperforms traditional methods and offers greater reliability for nonlinear dynamics. By adopting this flexible and robust technique, researchers can gain deeper insights into the complex interactions that drive biochemical systems.https://www.mdpi.com/2227-7390/11/14/3216biochemical systemnonlinear dynamicsneural networkSel’kov modelcoupled differential equations |
| spellingShingle | Jamshaid Ul Rahman Sana Danish Dianchen Lu Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis Mathematics biochemical system nonlinear dynamics neural network Sel’kov model coupled differential equations |
| title | Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis |
| title_full | Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis |
| title_fullStr | Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis |
| title_full_unstemmed | Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis |
| title_short | Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis |
| title_sort | deep neural network based simulation of sel kov model in glycolysis a comprehensive analysis |
| topic | biochemical system nonlinear dynamics neural network Sel’kov model coupled differential equations |
| url | https://www.mdpi.com/2227-7390/11/14/3216 |
| work_keys_str_mv | AT jamshaidulrahman deepneuralnetworkbasedsimulationofselkovmodelinglycolysisacomprehensiveanalysis AT sanadanish deepneuralnetworkbasedsimulationofselkovmodelinglycolysisacomprehensiveanalysis AT dianchenlu deepneuralnetworkbasedsimulationofselkovmodelinglycolysisacomprehensiveanalysis |