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Generally, the observation of life phenomena incurs certain costs and thus the number of sampling points in time is often small, as in the case of DNA microarray data. 1 For this reason, a reliable method of periodicity detection is needed for small datasets.
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Currently existing state-of-the-art tempo detection algorithms are generally speaking based on methods of periodicity detection.
On a method of investigating periodicities in disturbed series with special reference to Wolfer's sunspot numbers.
Training plan is based on the practice of method with a periodicity of 2 h per day.
However, as noted by Ptitsyn et al. [ 32], this method allows random re-institution of periodicity unless permutations in position of size p are avoided.
Finally, for the Periodic model, we varied the periodicity from 10.0 to 12.0 bp (corresponding roughly to the range of DNA helix), and for each of these values, we also varied the amplitude parameter, which is a measure of the strength of periodicity (see Methods).
In problems where the strength of periodicity is of interest, resampling methods are applicable.
The figures show that the proposed method generates the most accurate results in the sense of periodicity.
Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest.
For each TF, the method infers its activity profile across the cell cycle and then tests the significance of periodicity of the profile.
The significance of periodicity and enrichment of cell cycle genes can be calculated (see Methods and materials).
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