Dynamics modeling of genetic networks using genetic algorithm and S-system

Shinichi Kikuchi, Daisuke Tominaga, Masanori Arita, Katsutoshi Takahashi, Masaru Tomita

Research output: Contribution to journalArticle

319 Citations (Scopus)

Abstract

Motivation: The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. Results: The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

Original languageEnglish
Pages (from-to)643-650
Number of pages8
JournalBioinformatics
Volume19
Issue number5
DOIs
Publication statusPublished - 2003 Mar 22

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S-system
Genetic Network
Network Algorithms
Dynamic Modeling
Genetic algorithms
Genetic Algorithm
Network Structure
Fold
Feedback
Feedback Loop
Signal transduction
Function evaluation
Crossover
Optimization
Gene expression
Evolutionary algorithms
Dynamical systems
Predict
Signal Transduction
Metabolic Network

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Dynamics modeling of genetic networks using genetic algorithm and S-system. / Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru.

In: Bioinformatics, Vol. 19, No. 5, 22.03.2003, p. 643-650.

Research output: Contribution to journalArticle

Kikuchi, Shinichi ; Tominaga, Daisuke ; Arita, Masanori ; Takahashi, Katsutoshi ; Tomita, Masaru. / Dynamics modeling of genetic networks using genetic algorithm and S-system. In: Bioinformatics. 2003 ; Vol. 19, No. 5. pp. 643-650.
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