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Constructing gene regulatory networks from microarray data using GA/PSO with DTW
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DOI：10.1016/j.asoc.2011.11.013.png)
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Recently, many methods have been proposed for constructing gene regulatory networks (GRNs). However, most of the existing methods ignored the time delay regulatory relation in the GRN predictions. In this paper, we propose a hybrid method, termed GA/PSO with DTW, to construct GRNs from microarray datasets. The proposed method uses test of correlation coefficient and the dynamic time warping (DTW) algorithm to determine the existence of a time delay relation between two genes. In addition, it uses the particle swarm optimization (PSO) to find thresholds for discretizing the microarray dataset. Based on the discretized microarray dataset and the predicted types of regulatory relations among genes, the proposed method uses a genetic algorithm to generate a set of candidate GRNs from which the predicted GRN is constructed. Three real-life sub-networks of yeast are used to verify the performance of the proposed method. The experimental results show that the GA/PSO with DTW is better than the other existing methods in terms of predicting sensitivity and specificity. (C) 2011 Elsevier B.V. All rights reserved.
Keyword:
Gene regulatory networks
Genetic algorithms
Particle swarm optimization
Dynamic time warping
Microarray data analysis
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6.6
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1.4W
被引数:
4.8W
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