Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
In metabolic network modelling, the accuracy of kinetic parameters has become more important over the last two decades. Even a small perturbation in kinetic parameters may cause major changes in a model’s response. The focus of this study is to identify the kinetic parameters, using two distinct app...
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Scientific Research Publishing
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/9082/1/Large-scale%20kinetic%20parameter%20identification%20of%20metabolic%20network%20model%20of%20E.%20Coli%20using%20PSO.pdf http://umpir.ump.edu.my/id/eprint/9082/ http://dx.doi.org/10.4236/abb.2015.62012 |
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| author | Azrag, M. A. K. Tuty Asmawaty, Abdul Kadir Jaber, Aqeel S. Odili, Julius Beneoluchi |
| author_facet | Azrag, M. A. K. Tuty Asmawaty, Abdul Kadir Jaber, Aqeel S. Odili, Julius Beneoluchi |
| author_sort | Azrag, M. A. K. |
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| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In metabolic network modelling, the accuracy of kinetic parameters has become more important over the last two decades. Even a small perturbation in kinetic parameters may cause major changes in a model’s response. The focus of this study is to identify the kinetic parameters, using two distinct approaches: firstly, a One-at-a-Time Sensitivity Measure, performed on 185 kinetic parameters, which represent glycolysis, pentose phosphate, TCA cycle, gluconeogenesis, glycoxylate pathways, and acetate formation. Time profiles for sensitivity indices were calculated for each parameter. Seven kinetic parameters were found to be highly affected in the model response; secondly, particle swarm optimization was applied for kinetic parameter identification of a metabolic network model. The simulation results proved the effectiveness of the proposed method. |
| format | Article |
| id | my.ump.umpir.9082 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2015 |
| publisher | Scientific Research Publishing |
| record_format | eprints |
| spelling | my.ump.umpir.90822018-04-25T07:00:22Z http://umpir.ump.edu.my/id/eprint/9082/ Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO Azrag, M. A. K. Tuty Asmawaty, Abdul Kadir Jaber, Aqeel S. Odili, Julius Beneoluchi QA76 Computer software In metabolic network modelling, the accuracy of kinetic parameters has become more important over the last two decades. Even a small perturbation in kinetic parameters may cause major changes in a model’s response. The focus of this study is to identify the kinetic parameters, using two distinct approaches: firstly, a One-at-a-Time Sensitivity Measure, performed on 185 kinetic parameters, which represent glycolysis, pentose phosphate, TCA cycle, gluconeogenesis, glycoxylate pathways, and acetate formation. Time profiles for sensitivity indices were calculated for each parameter. Seven kinetic parameters were found to be highly affected in the model response; secondly, particle swarm optimization was applied for kinetic parameter identification of a metabolic network model. The simulation results proved the effectiveness of the proposed method. Scientific Research Publishing 2015 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/9082/1/Large-scale%20kinetic%20parameter%20identification%20of%20metabolic%20network%20model%20of%20E.%20Coli%20using%20PSO.pdf Azrag, M. A. K. and Tuty Asmawaty, Abdul Kadir and Jaber, Aqeel S. and Odili, Julius Beneoluchi (2015) Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO. Advances in Bioscience and Biotechnology, 6 (2). pp. 120-130. ISSN 2156-8456 (print); 2156-8502 (online). (Published) http://dx.doi.org/10.4236/abb.2015.62012 doi: 0.4236/abb.2015.62012 |
| spellingShingle | QA76 Computer software Azrag, M. A. K. Tuty Asmawaty, Abdul Kadir Jaber, Aqeel S. Odili, Julius Beneoluchi Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO |
| title | Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
|
| title_full | Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
|
| title_fullStr | Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
|
| title_full_unstemmed | Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
|
| title_short | Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO
|
| title_sort | large-scale kinetic parameter identification of metabolic network model of e. coli using pso |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/9082/1/Large-scale%20kinetic%20parameter%20identification%20of%20metabolic%20network%20model%20of%20E.%20Coli%20using%20PSO.pdf http://umpir.ump.edu.my/id/eprint/9082/ http://dx.doi.org/10.4236/abb.2015.62012 |
| url_provider | http://umpir.ump.edu.my/ |