2005
DOI: 10.1186/1471-2105-6-117
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Robust detection of periodic time series measured from biological systems

Abstract: Background: Periodic phenomena are widespread in biology. The problem of finding periodicity in biological time series can be viewed as a multiple hypothesis testing of the spectral content of a given time series. The exact noise characteristics are unknown in many bioinformatics applications. Furthermore, the observed time series can exhibit other non-idealities, such as outliers, short length and distortion from the original wave form. Hence, the computational methods should preferably be robust against such… Show more

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Cited by 111 publications
(68 citation statements)
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“…The time points were then permuted 50,000 times, and for each of the permutations, the Fourier transform was calculated together with the ratio of the F 24 Fourier component to the other components [52]. Expression data were fitted to a cosine curve.…”
Section: Methodsmentioning
confidence: 99%
“…The time points were then permuted 50,000 times, and for each of the permutations, the Fourier transform was calculated together with the ratio of the F 24 Fourier component to the other components [52]. Expression data were fitted to a cosine curve.…”
Section: Methodsmentioning
confidence: 99%
“…5E), which Tu et al confirmed to be in the top 4% of periodic genes in yeast. HSP12, along with 43% of the genes identified by MINE but not Spellman et al , was also in the top third of statistically significant periodic genes in yeast according to the more sophisticated specialty statistic of Ahdesmaki et al ., which was specifically designed for finding periodic relationships without a pre-specified frequency in biological systems (24). Due to MIC's generality and the small size of this dataset ( n =24), relatively few of the genes analyzed (5%) had significant MIC scores after multiple testing correction at a false discovery rate of 5%.…”
Section: Application Of Mine To Real Datasetsmentioning
confidence: 99%
“…None of the examples except for (F) and (G) were detected by Spellman's analysis. However, subsequent studies have shown that (C-E) are periodic genes with longer wavelengths (22, 24). More plots of genes detected using MIC and MAS are given in Fig.…”
Section: Figurementioning
confidence: 99%
“…Combined with a high level of stochastic noise, this makes the application of standard periodicity tests difficult due to insufficient statistical power. A number of algorithmic approaches have been applied recently to identify periodically expressed genes among thousands of time series profiles [8,9]. However, each of these methods only considers one gene expression profile at a time and lacks the statistical power to identify the circadian component in more than a small percentage of genes.…”
Section: Introductionmentioning
confidence: 99%