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

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)

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Metabolic Engineering, Metabolic Network, Dynamic Model, Sensitivity Analysis, Optimization and Estimation
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 24 Apr 2015 07:01
Last Modified: 25 Apr 2018 07:00
URI: http://umpir.ump.edu.my/id/eprint/9082
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