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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Main Authors:	Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S., Odili, Julius Beneoluchi
Format:	Article
Language:	English
Published:	Scientific Research Publishing 2015
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/1/Large-scale%20kinetic%20parameter%20identification%20of%20metabolic%20network%20model%20of%20E.%20Coli%20using%20PSO.pdf

id	ump-9082
recordtype	eprints
spelling	ump-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) http://dx.doi.org/10.4236/abb.2015.62012 doi: 0.4236/abb.2015.62012
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
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
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
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.
title	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_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_sort	large-scale kinetic parameter identification of metabolic network model of e. coli using pso
publisher	Scientific Research Publishing
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/ http://umpir.ump.edu.my/id/eprint/9082/1/Large-scale%20kinetic%20parameter%20identification%20of%20metabolic%20network%20model%20of%20E.%20Coli%20using%20PSO.pdf
first_indexed	2023-09-18T22:07:16Z
last_indexed	2023-09-18T22:07:16Z
_version_	1777414791689666560

Large-scale Kinetic Parameter Identification of Metabolic Network Model of E. coli using PSO

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