Spectral estimation in unevenly sampled space of periodically expressed microarray time series data |
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| Authors: | Alan Wee-Chung Liew Jun Xian Shuanhu Wu David Smith Hong Yan |
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| Affiliation: | (1) School of Information & Communication Technology, Griffith University, Brisbane, Australia;(2) Department of Electronic Engineering, City University of Hong Kong, Hong Kong, Hong Kong;(3) Department of Mathematics, Sun Yat-sen University, Guangzhou, 510275, China;(4) School of Computer Science and Technology, Yantai University, Yantai, 264005, China;(5) Department of Biochemistry, University of Hong Kong, Pok Fu Lam, Hong Kong;(6) School of Electronic and Information Engineering, University of Sydney, NSW, 2006 Sydney, Australia |
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| Abstract: | Background Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically expressed. Such challenge occurs due to the fact that the observed time series usually exhibit non-idealities, such as noise, short length, and unevenly sampled time points. Most methods used in the literature operate on evenly sampled time series and are not suitable for unevenly sampled time series. |
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