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Depositordc.contributorZielinski, Tomasz
Funderdc.contributor.otherBBSRC - Biotechnology and Biological Sciences Research Councilen_UK
Data Creatordc.creatorZielinski, Tomasz
Data Creatordc.creatorMillar, Andrew J
Date Accessioneddc.date.accessioned2019-10-22T09:29:47Z
Date Availabledc.date.available2019-10-22T09:29:47Z
Citationdc.identifier.citationZielinski, Tomasz; Millar, Andrew J. (2019). Timeseries used in Zielinski et al. Strengths and Limitations of Period Estimation Methods, [dataset]. University of Edinburgh, School of Biological Sciences and SynthSys. https://doi.org/10.7488/ds/2636.en
Persistent Identifierdc.identifier.urihttp://hdl.handle.net/10283/3432
Persistent Identifierdc.identifier.urihttps://doi.org/10.7488/ds/2636
Dataset Description (abstract)dc.description.abstractDataset contains timeseries data used for testing period analysis methods. The full details of the data are described in the actual paper, here there is only a short summary of methods generation. The synthetic test signals comprise: - a pure cosine of known frequency, and hence known period; - a pulsed waveform which comprises pulses of a Gaussian waveform with a standard deviation of (period/7); - a double pulsed waveform which comprises two periodic Gaussian waveforms; - simulated clock data generated using a delayed negative feedback loop (DNFL) model. Here we use parameter sets identical to those used in Costa MJ et al. Biostatistics 2013 to produce two sets with moderate level of asymmetry or a moderate shoulder. Once the basic time series had been generated, noise was added. The noise was additive and was either uniform noise or walking noise. Uniform noise is drawn from a uniform distribution and the amplitude of the noise is defined as a percentage of the amplitude of the original time-series. This would be characteristic of the noise in a measurement system. Walking noise is additive and uniform, but this time the distribution of the noise is restricted so that the current data point lies within a limited range of the previous data point. To assess applicability of the methods to the analysis of real biological systems, we also tested data sets obtained by in vivo imaging of transgenic Arabidopsis thaliana plants.en_UK
Dataset Description (TOC)dc.description.tableofcontents* "synthetic data noise.zip" - generated data with uniform noise added. Each signal waveform is in a separate subfolder, which then contain data groups but noise level and timeseries duration (in days) ; * "synthetic data wnoise.zip" - generated data with "walking" noise added. Each signal waveform is in a separate subfolder, which then contain data groups but noise level and timeseries duration (in days) ; * "bio data.zip" - examples of biological data ; * "amp trends.zip" - data with amplitude dampening, organized in subfolders by signal waveform and dampening pattern ; * "base trends.zip" - data with baseline trends added, organized in subfolders by trend pattern. The files with suffix "results" contains results of period analysis for the datasets with BioDare methods.en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburgh, School of Biological Sciences and SynthSysen_UK
Relation (Is Referenced By)dc.relation.isreferencedbyhttps://doi.org/10.1371/journal.pone.0096462en_UK
Relation (Is Referenced By)dc.relation.isreferencedbyhttps://europepmc.org/abstract/MED/24809473en_UK
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Subjectdc.subjectcircadianen_UK
Subjectdc.subjectbiological rhythmsen_UK
Subjectdc.subjecttimeseriesen_UK
Subjectdc.subjecttime seriesen_UK
Subject Classificationdc.subject.classificationBiological Sciences::Others in Biological Sciencesen_UK
Titledc.titleTimeseries used in Zielinski et al. Strengths and Limitations of Period Estimation Methodsen_UK
Alternative Titledc.title.alternativeStrengths and Limitations of Period Estimation Methods for Circadian Dataen_UK
Alternative Titledc.title.alternativeCircadian timeseries data for testing methods of periods analysisen_UK
Typedc.typedataseten_UK

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