Parameter estimation using Improved Differential Evolution (IDE) and bacterial foraging algorithm to model tyrosine production in Mus Musculus (Mouse)

Jia Xing Yeoh, Chuii Khim Chong, Yee Wen Choon, Lian En Chai, Safaai Deris, Rosli Md Illias, Mohd Saberi Mohamad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimization method that is implemented in this research to obtain the best kinetic parameter value. The proposed algorithm is then used to model tyrosine production in mus musculus (mouse) by using a dataset, JAK/STAT (Janus Kinase Signal Transducer and Activator of Transcription) signal transduction pathway. Global optimization is a method to identify the optimal kinetic parameter using ordinary differential equation. From the ordinary parameter of biomathematical field, there are many unknown parameters and commonly the parameters are in nonlinear form. Global optimization method includes differential evolution algorithm which will be used in this research. Kalman Filter and Bacterial Foraging algorithm help in handling noise data and faster convergences respectively in the conventional Differential Evolution. The results from this experiment show estimatedly optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.

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
Pages179-190
Number of pages12
DOIs
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

Conference

Conference17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013
Country/TerritoryAustralia
CityGold Coast, QLD
Period4/14/134/17/13

Keywords

  • Bacterial foraging algorithm
  • Differential evolution algorithm
  • Kalman filtering algorithm
  • Modeling
  • Parameter estimation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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