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Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent years,...
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Related Experiment Video

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Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
09:35

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Published on: March 10, 2017

WAVECLOCK: wavelet analysis of circadian oscillation.

Tom S Price1, Julie E Baggs, Anne M Curtis

  • 1Institute of Psychiatry, Kings College London. thomas.price@iop.kcl.ac.uk

Bioinformatics (Oxford, England)
|October 22, 2008
PubMed
Summary

This study introduces a new method to analyze circadian rhythms in cell lines, addressing variability and non-stationarity. The technique uses continuous wavelet decomposition to accurately model changes in oscillation amplitude and period.

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Area of Science:

  • * Molecular biology
  • * Chronobiology
  • * Data analysis

Background:

  • * Circadian clock gene and protein oscillations are measurable in vitro using synchronized cell lines.
  • * These biological rhythms exhibit significant variability and non-stationarity, influenced by culture conditions, baseline trends, damping, and period drift.
  • * Accurate characterization of these rhythms is crucial for understanding cellular timekeeping.

Purpose of the Study:

  • * To develop a robust technique for analyzing non-stationary oscillations in circadian clock components.
  • * To provide a method for characterizing modal frequencies, amplitude, and period changes over time.
  • * To address limitations of traditional methods in handling variability and noise in biological rhythms.

Main Methods:

  • * Utilized continuous wavelet decomposition for non-parametric modeling of oscillations.
  • * Applied the technique to analyze in vitro synchronized cell line data.
  • * Developed the 'waveclock' R package for method implementation and accessibility.

Main Results:

  • * The continuous wavelet decomposition method effectively models changes in amplitude and period of circadian oscillations.
  • * The technique successfully removes baseline effects and noise, improving rhythm characterization.
  • * Modal frequencies of oscillation are accurately identified, even with non-stationary data.

Conclusions:

  • * The presented technique offers a powerful approach for analyzing complex circadian rhythms in vitro.
  • * The 'waveclock' R package provides a readily available tool for researchers studying biological oscillations.
  • * This method enhances the reliability and accuracy of circadian rhythm analysis in cell-based assays.