title: 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.
authors.affiliation: Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China. h.yan@cityu.edu.hk
authors.forename: Hong
authors.initials: H
authors.lastname: Yan
authors.forename: Tuan
authors.initials: T
authors.lastname: Pham
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D013057:Spectrum Analysis / Q000379:methods