Periodicity detection in small-sample gene-expression data

被引:1
|
作者
Mahata, Kaushik [1 ]
Mahata, Pritha [1 ]
机构
[1] Univ Newcastle, Sch Elect Engn & Comp Sci, Newcastle, NSW 2308, Australia
来源
PROCEEDINGS OF THE 2007 15TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING | 2007年
关键词
time-series microarray data; periodicity; convex optimization;
D O I
10.1109/ICDSP.2007.4288531
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Analysis of cell-cycle regulation, circadian rhythms, ovarian cycle, etc. demands finding periodicity in the biological data. In this work, we will consider gene expression data, which is usually quite noisy and comprise of small number of samples from very few periods (2-3). We propose 1 non-parametric method for detecting the period and shape of the periodic signals (e.g., gene expressions for cell-cycles). We use a quadratic-optimization problem formulation in order to find the shape of the signal and the, properties of periodicity to find the exact period. Finally, we show the results of applying this method on the gene expression data for human fibroblast cell cycles.
引用
收藏
页码:111 / +
页数:2
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