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 proceedingConference contribution

1 Citation (Scopus)


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 languageEnglish
Title of host publicationTrends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops
Subtitle of host publicationDMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Revised Selected Papers
Number of pages10
Publication statusPublished - 2013
Externally publishedYes
Event17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013 - Gold Coast, QLD, Australia
Duration: Apr 14 2013Apr 17 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7867 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013
CityGold Coast, QLD


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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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