Periodicity Identification of Microarray Time Series Data based on Spectral Analysis

In this paper, we propose spectral analysis method to identify periodically expressed genes in microarray data using a forward and backward linear prediction (FBLP) model and the singular value decomposition (SVD) (FBLP-SVD) algorithm. The spectrum-mean-subtraction method is employed prior to this analysis as a pre-filtering procedure. The combination of the spectrum-mean-subtraction and FBLP-SVD algorithm offers a effective tool for periodicity identification. Using our technique, more genes have been successful identified as periodic genes in the genome of Saccharomyces cerevisiae.