An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

Background: Mathematical models play a central role in facilitating researchers to better understand and comprehensively analyze various processes in biochemical systems. Their usage is beneficial in metabolic engineering as they help predict and improve desired products. However, one of the primary...

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Main Authors: Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis
Format: Article
Language:English
Published: Bentham Science Publishers 2019
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/1/An%20Improved%20Scatter%20Search%20Algorithm%20for%20Parameter%20Estimation1.pdf
id ump-25105
recordtype eprints
spelling ump-251052019-06-18T07:59:58Z http://umpir.ump.edu.my/id/eprint/25105/ An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems Muhammad Akmal, Remli Mohd Saberi, Mohamad Safaai, Deris Sinnott, Richard O. Suhaimi, Napis QA75 Electronic computers. Computer science Background: Mathematical models play a central role in facilitating researchers to better understand and comprehensively analyze various processes in biochemical systems. Their usage is beneficial in metabolic engineering as they help predict and improve desired products. However, one of the primary challenges in model building is parameter estimation. It is the process to find nearoptimal values of kinetic parameters which may culminate in the best fit of model prediction to experimental data. Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. The improved algorithm is based on hybridization of quasi oppositionbased learning in enhanced scatter search (QOBLESS) method. The algorithm is tested using a largescale metabolic model of Chinese Hamster Ovary (CHO) cells. Results: The experiment result shows that the proposed algorithm performs better than other algorithms in terms of convergence speed and the minimum value of the objective function (loglikelihood). The estimated parameters from the experiment produce a better model by means of obtaining a reasonable good fit of model prediction to the experimental data Conclusion: The kinetic parameters’ value obtained from our work was able to result in a reasonable best fit of model prediction to the experimental data, which contributes to a better understanding and produced more accurate model. Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building. Bentham Science Publishers 2019 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25105/1/An%20Improved%20Scatter%20Search%20Algorithm%20for%20Parameter%20Estimation1.pdf Muhammad Akmal, Remli and Mohd Saberi, Mohamad and Safaai, Deris and Sinnott, Richard O. and Suhaimi, Napis (2019) An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems. Current Proteomics, 16 (5). pp. 425-436. ISSN 1570-1646 http://www.eurekaselect.com/171196 https://doi.org/10.2174/1570164616666190401203128
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Muhammad Akmal, Remli
Mohd Saberi, Mohamad
Safaai, Deris
Sinnott, Richard O.
Suhaimi, Napis
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
description Background: Mathematical models play a central role in facilitating researchers to better understand and comprehensively analyze various processes in biochemical systems. Their usage is beneficial in metabolic engineering as they help predict and improve desired products. However, one of the primary challenges in model building is parameter estimation. It is the process to find nearoptimal values of kinetic parameters which may culminate in the best fit of model prediction to experimental data. Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. The improved algorithm is based on hybridization of quasi oppositionbased learning in enhanced scatter search (QOBLESS) method. The algorithm is tested using a largescale metabolic model of Chinese Hamster Ovary (CHO) cells. Results: The experiment result shows that the proposed algorithm performs better than other algorithms in terms of convergence speed and the minimum value of the objective function (loglikelihood). The estimated parameters from the experiment produce a better model by means of obtaining a reasonable good fit of model prediction to the experimental data Conclusion: The kinetic parameters’ value obtained from our work was able to result in a reasonable best fit of model prediction to the experimental data, which contributes to a better understanding and produced more accurate model. Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.
format Article
author Muhammad Akmal, Remli
Mohd Saberi, Mohamad
Safaai, Deris
Sinnott, Richard O.
Suhaimi, Napis
author_facet Muhammad Akmal, Remli
Mohd Saberi, Mohamad
Safaai, Deris
Sinnott, Richard O.
Suhaimi, Napis
author_sort Muhammad Akmal, Remli
title An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
title_short An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
title_full An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
title_fullStr An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
title_full_unstemmed An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
title_sort improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
publisher Bentham Science Publishers
publishDate 2019
url http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/
http://umpir.ump.edu.my/id/eprint/25105/1/An%20Improved%20Scatter%20Search%20Algorithm%20for%20Parameter%20Estimation1.pdf
first_indexed 2023-09-18T22:38:22Z
last_indexed 2023-09-18T22:38:22Z
_version_ 1777416748860964864

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