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Parameter Estimation for Simulation of Glycolysis Pathway by Using an Improved Differential Evolution

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Knowledge Technology (KTW 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 295))

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Abstract

An improved differential evolution (DE) algorithm is proposed in this paper to optimize its performance in estimating the germane parameters for metabolic pathway data to simulate glycolysis pathway for Saccharomyces cerevisiae. This study presents an improved algorithm of parameter sensitivity test into the process of DE algorithm. The result of the improved algorithm is testifying to be supreme to the others estimation algorithms. The outcomes from this study promote estimating optimal kinetic parameters, shorter computation time and ameliorating the precision of simulated kinetic model for the experimental data.

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References

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Author information

Authors and Affiliations

  1. Artificial Intelligence and Bioinformatics Research Group, Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

    Chuii Khim Chong, Mohd Saberi Mohamad, Safaai Deris, Yee Wen Choon & Lian En Chai

Authors
  1. Chuii Khim Chong
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  2. Mohd Saberi Mohamad
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  3. Safaai Deris
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  4. Yee Wen Choon
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  5. Lian En Chai
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Editor information

Editors and Affiliations

  1. MIMOS Berhad, Knowledge Technology, Technology Park Malaysia, 57000, Kuala Lumpur, Malaysia

    Dickson Lukose

  2. Department of Systems and Network,College of Information Technology, Jalan IKRAM-UNITEN, Universiti Tenaga Nasional, 43000, Kajang, Malaysia

    Abdul Rahim Ahmad  & Azizah Suliman  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Chong, C.K., Mohamad, M.S., Deris, S., Choon, Y.W., Chai, L.E. (2012). Parameter Estimation for Simulation of Glycolysis Pathway by Using an Improved Differential Evolution. In: Lukose, D., Ahmad, A.R., Suliman, A. (eds) Knowledge Technology. KTW 2011. Communications in Computer and Information Science, vol 295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32826-8_37

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  • DOI: https://doi.org/10.1007/978-3-642-32826-8_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32825-1

  • Online ISBN: 978-3-642-32826-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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