191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation

Chuii Khim Chong; Mohd Saberi Mohamad; Safaai Deris; Mohd Shahir Shamsir; Yee Wen Choon; Lian En Chai

doi:10.1007/978-3-642-40319-4_17

191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

When analysing a metabolic pathway through mathematical model, it is important that the significant parameters are being correctly estimated. However, this process often comes across problems such aseasily being trapped in local minima, repetitive exposure to worse results during the search process, and occurrence of noisy data. Thus, an improved Bee Memory Differential Evolution algorithm (IBMDE), which is a hybrid of the Differential Evolution algorithm (DE), the Kalman Filter (KF), Artificial Bee Colony algorithm (ABC), and a memory feature is presented this paper. IBMDE is an improved estimation algorithm as previous work only utilised DE. The threonine biosynthesis pathway is the metabolic pathways used in this paper. For metabolite O-Phosphohomoserine production simulation, the IBMDE able to produce the estimated optimal kinetic parameter values with significantly reduced error rate (63.67%) and shows a faster convergence time (71.46%) compared to the Nelder Mead (NM), the Simulated Annealing (SA), the Genetic Algorithm (GA), and DE respectively. In addition, IBMDE demostrates to be a reliable estimation algorithm.

Original language	English
Title of host publication	Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops
Subtitle of host publication	DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers
Pages	191-200
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-40319-4_17
Publication status	Published - 2013
Externally published	Yes
Event	17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013 - Gold Coast, QLD, Australia Duration: Apr 14 2013 → Apr 17 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7867 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013
Country/Territory	Australia
City	Gold Coast, QLD
Period	4/14/13 → 4/17/13

Keywords

Artificial bee colony algorithm
Differential evolution algorithm
Kalman filter
Memory feature
Parameter estimation

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-40319-4_17

Cite this

Chong, C. K., Mohamad, M. S., Deris, S., Shamsir, M. S., Choon, Y. W., & Chai, L. E. (2013). 191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation. In Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers (pp. 191-200). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7867 LNAI). https://doi.org/10.1007/978-3-642-40319-4_17

191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation. / Chong, Chuii Khim; Mohamad, Mohd Saberi; Deris, Safaai et al.
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers. 2013. p. 191-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7867 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chong, CK, Mohamad, MS, Deris, S, Shamsir, MS, Choon, YW & Chai, LE 2013, 191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation. in Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7867 LNAI, pp. 191-200, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, Gold Coast, QLD, Australia, 4/14/13. https://doi.org/10.1007/978-3-642-40319-4_17

Chong CK, Mohamad MS, Deris S, Shamsir MS, Choon YW, Chai LE. 191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation. In Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers. 2013. p. 191-200. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-40319-4_17

Chong, Chuii Khim ; Mohamad, Mohd Saberi ; Deris, Safaai et al. / 191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation. Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers. 2013. pp. 191-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - When analysing a metabolic pathway through mathematical model, it is important that the significant parameters are being correctly estimated. However, this process often comes across problems such aseasily being trapped in local minima, repetitive exposure to worse results during the search process, and occurrence of noisy data. Thus, an improved Bee Memory Differential Evolution algorithm (IBMDE), which is a hybrid of the Differential Evolution algorithm (DE), the Kalman Filter (KF), Artificial Bee Colony algorithm (ABC), and a memory feature is presented this paper. IBMDE is an improved estimation algorithm as previous work only utilised DE. The threonine biosynthesis pathway is the metabolic pathways used in this paper. For metabolite O-Phosphohomoserine production simulation, the IBMDE able to produce the estimated optimal kinetic parameter values with significantly reduced error rate (63.67%) and shows a faster convergence time (71.46%) compared to the Nelder Mead (NM), the Simulated Annealing (SA), the Genetic Algorithm (GA), and DE respectively. In addition, IBMDE demostrates to be a reliable estimation algorithm.

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191-200 Threonine biosynthesis pathway simulation using IBMDE with parameter estimation

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