Spectral similarity for analysis of DNA microarray time-series data

Abstract

This paper proposes a new similarity measurement for comparison and analysis of DNA microarray time-series data. In this method, a gene expression time series is decomposed into frequency components and the correlation between the data from a pair of genes is measured in the frequency domain. The method effectively solves the phase delay problem and provides a more accurate metric for microarray time-series classification.