Robust detection of periodic time series measured from biological systems |
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Authors: | Miika?Ahdesm?ki Email author" target="_blank">Harri?L?hdesm?kiEmail author Ron?Pearson Heikki?Huttunen Olli?Yli-Harja |
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Institution: | (1) Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland;(2) ProSanos Corporation, Harrisburg, PA 17101, USA |
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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 anomalies in the data. |
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Keywords: | |
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