{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T23:50:22Z","timestamp":1774741822383,"version":"3.50.1"},"reference-count":21,"publisher":"Oxford University Press (OUP)","issue":"24","funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,12,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: To discover and study periodic processes in biological systems, we sought to identify periodic patterns in their gene expression data. We surveyed a large number of available methods for identifying periodicity in time series data and chose representatives of different mathematical perspectives that performed well on both synthetic data and biological data. Synthetic data were used to evaluate how each algorithm responds to different curve shapes, periods, phase shifts, noise levels and sampling rates. The biological datasets we tested represent a variety of periodic processes from different organisms, including the cell cycle and metabolic cycle in Saccharomyces cerevisiae, circadian rhythms in Mus musculus and the root clock in Arabidopsis thaliana.<\/jats:p><jats:p>Results: From these results, we discovered that each algorithm had different strengths. Based on our findings, we make recommendations for selecting and applying these methods depending on the nature of the data and the periodic patterns of interest. Additionally, these results can also be used to inform the design of large-scale biological rhythm experiments so that the resulting data can be used with these algorithms to detect periodic signals more effectively.<\/jats:p><jats:p>Contact: \u00a0anastasia.deckard@duke.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt541","type":"journal-article","created":{"date-parts":[[2013,9,21]],"date-time":"2013-09-21T04:54:29Z","timestamp":1379739269000},"page":"3174-3180","source":"Crossref","is-referenced-by-count":89,"title":["Design and analysis of large-scale biological rhythm studies: a comparison of algorithms for detecting periodic signals in biological data"],"prefix":"10.1093","volume":"29","author":[{"given":"Anastasia","family":"Deckard","sequence":"first","affiliation":[{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"},{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ron C.","family":"Anafi","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John B.","family":"Hogenesch","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven B.","family":"Haase","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Harer","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology and Bioinformatics, 2Department of Mathematics, Duke University, Durham, NC 27708, USA, 3Department of Medicine, 4Department of Pharmacology, Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA and 5Department of Biology, Duke University, Durham, NC 27708, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,9,20]]},"reference":[{"key":"2023012810483029100_btt541-B1","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1093\/bioinformatics\/btl121","article-title":"Unbiased pattern detection in microarray data series","volume":"22","author":"Ahnert","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012810483029100_btt541-B2","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. 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