Abstract
Mathematical models of metabolic processes are the cornerstone of computational systems biology. In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. The common way of estimating the parameters is to formulate it as an optimization problem. Global optimization methods can be applied by minimizing the distance between experimental data and predicted models. This paper proposes the Hybrid of Bees Algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. The performance of the BAHS is evaluated and compared with other algorithms. The results show that BAHS performed better as it improved the performance of the original BA by 60%. Meanwhile, it takes less computational time to estimate the kinetics parameters of essential amino acid production for Arabidopsis thaliana.
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Acknowledgements
We would like to thank Malaysian Ministry of Higher Education and Universiti Teknologi Malaysia for supporting this research by the Fundamental Research Grant Schemes (grant number: R.J130000.7828.4F886 and R.J130000.7828.4F720). We would also like to thank Universiti Malaysia Pahang for sponsoring this research via the RDU Grant (Grant Number: RDU180307).
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Aw, M.Y. et al. (2019). Parameter Estimation of Essential Amino Acids in Arabidopsis thaliana Using Hybrid of Bees Algorithm and Harmony Search. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., González, P. (eds) Practical Applications of Computational Biology and Bioinformatics, 12th International Conference. PACBB2018 2018. Advances in Intelligent Systems and Computing, vol 803. Springer, Cham. https://doi.org/10.1007/978-3-319-98702-6_2
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DOI: https://doi.org/10.1007/978-3-319-98702-6_2
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