title: An intelligent two-stage evolutionary algorithm for dynamic pathway identification from gene expression profiles.
abstract: From gene expression profiles, it is desirable to rebuild cellular dynamic regulation networks to discover more delicate and substantial functions in molecular biology, biochemistry, bioengineering and pharmaceutics. S-system model is suitable to characterize biochemical network systems and capable to analyze the regulatory system dynamics. However, inference of an S-system model of N-gene genetic networks has 2N(N+1) parameters in a set of non-linear differential equations to be optimized. This paper proposes an intelligent two-stage evolutionary algorithm (iTEA) to efficiently infer the S-system models of genetic networks from time-series data of gene expression. To cope with curse of dimensionality, the proposed algorithm 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). At the second stage, the obtained N solutions to the N subproblems are combined and refined using an OED-based simulated annealing algorithm for handling noisy gene expression profiles. The effectiveness of iTEA is evaluated using simulated expression patterns with and without noise running on a single-processor PC. It is shown that 1) IGA is efficient enough to solve subproblems; 2) IGA is significantly superior to the existing method SPXGA; and 3) iTEA performs well in inferring S-system models for dynamic pathway identification.
authors.forename: Shinn-Ying
authors.initials: SY
authors.lastname: Ho
authors.forename: Chih-Hung
authors.initials: CH
authors.lastname: Hsieh
authors.forename: Fu-Chieh
authors.initials: FC
authors.lastname: Yu
authors.forename: Hui-Ling
authors.initials: HL
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001698:Biomedical Engineering / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D019143:Evolution, Molecular; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D025941:Protein Interaction Mapping; D012984:Software