Skip to main navigation Skip to search Skip to main content

Periodicity identification of microarray time series data based on spectral analysis

Miew Keen Choong, Kong Chen Lye, David Levy, Hong Yan

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

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. © 2006 IEEE.
Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages1281-1285
Volume2
DOIs
Publication statusPublished - 2007
Event2006 IEEE International Conference on Systems, Man and Cybernetics (SMC'06) - The Grand Hotel, Taipei, Taiwan, China
Duration: 8 Oct 200611 Oct 2006

Publication series

Name
Volume2
ISSN (Print)1062-922X

Conference

Conference2006 IEEE International Conference on Systems, Man and Cybernetics (SMC'06)
Abbreviated titleSMC 2006
PlaceTaiwan, China
CityTaipei
Period8/10/0611/10/06

Fingerprint

Dive into the research topics of 'Periodicity identification of microarray time series data based on spectral analysis'. Together they form a unique fingerprint.

Cite this