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Similarity Analysis of Time Series Gene Expression using Dual-Tree Wavelet Transform

This study presents a similarity-determining method for measuring regulatory relationships between pairs of genes from microarray time series data. The proposed similarity metrics are based on a new method to measure structural similarity to compare the quality of images. We make use of the fact that dual-tree wavelet transform (DTWT) can provide approximate shift invariance and maintain the structures between pairs of regulation-related time series expression data. Despite the simplicity of the presented method, experimental results demonstrate that it enhances the similarity index when tested on known transcriptional regulatory genes.