Evolutionary divide-and-conquer approach to inferring S-system models of genetic networks

Shinn-Ying Ho*, Chih Hung Hsieh, Fu Chieh Yu, Hui Ling Huang

*Corresponding author for this work

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

2 Scopus citations

Abstract

This paper proposes an efficient evolutionary divide-and-conquer approach (EDACA) to inferring S-system models of genetic networks from time-series data of gene expression. Inference of an S-system model has 2N(N+1) parameters to be optimized where N is the number of genes in a genetic network. To cope with higher dimensionality, the proposed approach consists of two stages where each uses a divide-and-conquer strategy. The optimization problem is first decomposed into N subproblems having 2(N+1) parameters each. At the first stage, each subproblem is solved using a novel intelligent genetic algorithm (IGA) with intelligent crossover based on orthogonal experimental design (OED). The intelligent crossover divides two parents into n pairs of parameter groups, economically identifies the potentially better one of two groups of each pair, and systematically obtains a potentially good approximation to the best one of all 2n combinations using at most 2n function evaluations. At the second stage, the obtained N solutions to the N subproblems are combined and refined using an OED-based simulated annealing algorithm (OSA) for handling noisy gene expression data. The effectiveness of EDACA is evaluated using simulated expression patterns with/without noise running on a single-CPU PC. It is shown that: 1) IGA is efficient enough to solve subproblems; 2) IGA is significantly superior to the existing method of using GA with simplex crossover; and 3) EDACA performs well in inferring S-system models of genetic networks from small-noise gene expression data.

Original languageEnglish
Title of host publication2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
Pages691-698
Number of pages8
DOIs
StatePublished - 31 Oct 2005
Event2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland, United Kingdom
Duration: 2 Sep 20055 Sep 2005

Publication series

Name2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
Volume1

Conference

Conference2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005
CountryUnited Kingdom
CityEdinburgh, Scotland
Period2/09/055/09/05

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