About: Optimal time frequency analysis for biological data

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Optimal time frequency analysis for biological data - pyBOAT
Creator	Granada, Adrián Mönke, Gregor Schmal, Christoph Sorgenfrei, Frieda
source	BioRxiv
abstract	Methods for the quantification of rhythmic biological signals have been essential for the discovery of function and design of biological oscillators. Advances in live measurements have allowed recordings of unprecedented resolution revealing a new world of complex heterogeneous oscillations with multiple noisy non-stationary features. However, our understanding of the underlying mechanisms regulating these oscillations has been lagging behind, partially due to the lack of simple tools to reliably quantify these complex non-stationary features. With this challenge in mind, we have developed pyBOAT, a Python-based fully automatic stand-alone software that integrates multiple steps of non-stationary oscillatory time series analysis into an easy-to-use graphical user interface. pyBOAT implements continuous wavelet analysis which is specifically designed to reveal time-dependent features. In this work we illustrate the advantages of our tool by analyzing complex non-stationary time-series profiles. Our approach integrates data-visualization, optimized sinc-filter detrending, amplitude envelope removal and a subsequent continuous-wavelet based time-frequency analysis. Finally, using analytical considerations and numerical simulations we discuss unexpected pitfalls in commonly used smoothing and detrending operations.
has issue date	2020-06-04(xsd:dateTime)
bibo:doi	10.1101/2020.04.29.067744
has license	biorxiv
sha1sum (hex)	0ad95c7b1ad6f923d80105aee84c29f68bf92c3b
schema:url	https://doi.org/10.1101/2020.04.29.067744
resource representing a document's title	Optimal time frequency analysis for biological data - pyBOAT
schema:publication	bioRxiv
resource representing a document's body	covid:0ad95c7b1ad6f923d80105aee84c29f68bf92c3b#body_text
is schema:about of	named entity 'complex' named entity 'wavelet' named entity 'non-stationary' named entity 'signals' named entity 'amplitude' »more»

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