Periodicity identification of microarray time series data based on spectral analysis

被引：1
作者：
Choong, Miew Keen [1 ]
Lye, Kong Chen [2 ]
Levy, David [1 ]
Yan, Hong [3 ,4 ]
机构：
[1] Univ Sydney, Sch Elect & Informat, Sydney, NSW 2006, Australia
[2] Card Access Services, Sydney, NSW, Australia
[3] City Univ Hong Kong, Kowloon, Peoples R China
[4] Univ Sydney, Sydney, NSW 2006, Australia
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS | 2006年
关键词：
D O I：
10.1109/ICSMC.2006.384891
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1281 / +
页数：4
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