ArticlePloS one2014
Optimal experimental design to estimate statistically significant periods of oscillations in time course data.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Prolactin blood concentration relies on the scalability of the TIDA neurons' network efficiencyiScience · 2024Article
- Computational Approaches and Tools as Applied to the Study of Rhythms and Chaos in Biology.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Sperm physiology varies according to ultradian and infradian rhythms.Scientific reports · 2019Article
- The fractal organization of ultradian rhythms in avian behavior.Scientific reports · 2017Article
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Authors and funding
3 authors.
Funding
Abstract
We investigated commonly used methods (Autocorrelation, Enright, and Discrete Fourier Transform) to estimate the periodicity of oscillatory data and determine which method most accurately estimated periods while being least vulnerable to the presence of noise. Both simulated and experimental data were used in the analysis performed. We determined the significance of calculated periods by applying these methods to several random permutations of the data and then calculating the probability of obtaining the period's peak in the corresponding periodograms. Our analysis suggests that the Enright method is the most accurate for estimating the period of oscillatory data. We further show that to accurately estimate the period of oscillatory data, it is necessary that at least five cycles of data are sampled, using at least four data points per cycle. These results suggest that the Enright method should be more widely applied in order to improve the analysis of oscillatory data.
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