Cargando…
Signal analysis of behavioral and molecular cycles
BACKGROUND: Circadian clocks are biological oscillators that regulate molecular, physiological, and behavioral rhythms in a wide variety of organisms. While behavioral rhythms are typically monitored over many cycles, a similar approach to molecular rhythms was not possible until recently; the adven...
Autores principales: | , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2002
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC65508/ https://www.ncbi.nlm.nih.gov/pubmed/11825337 http://dx.doi.org/10.1186/1471-2202-3-1 |
_version_ | 1782120160185810944 |
---|---|
author | Levine, Joel D Funes, Pablo Dowse, Harold B Hall, Jeffrey C |
author_facet | Levine, Joel D Funes, Pablo Dowse, Harold B Hall, Jeffrey C |
author_sort | Levine, Joel D |
collection | PubMed |
description | BACKGROUND: Circadian clocks are biological oscillators that regulate molecular, physiological, and behavioral rhythms in a wide variety of organisms. While behavioral rhythms are typically monitored over many cycles, a similar approach to molecular rhythms was not possible until recently; the advent of real-time analysis using transgenic reporters now permits the observations of molecular rhythms over many cycles as well. This development suggests that new details about the relationship between molecular and behavioral rhythms may be revealed. Even so, behavioral and molecular rhythmicity have been analyzed using different methods, making such comparisons difficult to achieve. To address this shortcoming, among others, we developed a set of integrated analytical tools to unify the analysis of biological rhythms across modalities. RESULTS: We demonstrate an adaptation of digital signal analysis that allows similar treatment of both behavioral and molecular data from our studies of Drosophila. For both types of data, we apply digital filters to extract and clarify details of interest; we employ methods of autocorrelation and spectral analysis to assess rhythmicity and estimate the period; we evaluate phase shifts using crosscorrelation; and we use circular statistics to extract information about phase. CONCLUSION: Using data generated by our investigation of rhythms in Drosophila we demonstrate how a unique aggregation of analytical tools may be used to analyze and compare behavioral and molecular rhythms. These methods are shown to be versatile and will also be adaptable to further experiments, owing in part to the non-proprietary nature of the code we have developed. |
format | Text |
id | pubmed-65508 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2002 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-655082002-02-14 Signal analysis of behavioral and molecular cycles Levine, Joel D Funes, Pablo Dowse, Harold B Hall, Jeffrey C BMC Neurosci Methodology Article BACKGROUND: Circadian clocks are biological oscillators that regulate molecular, physiological, and behavioral rhythms in a wide variety of organisms. While behavioral rhythms are typically monitored over many cycles, a similar approach to molecular rhythms was not possible until recently; the advent of real-time analysis using transgenic reporters now permits the observations of molecular rhythms over many cycles as well. This development suggests that new details about the relationship between molecular and behavioral rhythms may be revealed. Even so, behavioral and molecular rhythmicity have been analyzed using different methods, making such comparisons difficult to achieve. To address this shortcoming, among others, we developed a set of integrated analytical tools to unify the analysis of biological rhythms across modalities. RESULTS: We demonstrate an adaptation of digital signal analysis that allows similar treatment of both behavioral and molecular data from our studies of Drosophila. For both types of data, we apply digital filters to extract and clarify details of interest; we employ methods of autocorrelation and spectral analysis to assess rhythmicity and estimate the period; we evaluate phase shifts using crosscorrelation; and we use circular statistics to extract information about phase. CONCLUSION: Using data generated by our investigation of rhythms in Drosophila we demonstrate how a unique aggregation of analytical tools may be used to analyze and compare behavioral and molecular rhythms. These methods are shown to be versatile and will also be adaptable to further experiments, owing in part to the non-proprietary nature of the code we have developed. BioMed Central 2002-01-18 /pmc/articles/PMC65508/ /pubmed/11825337 http://dx.doi.org/10.1186/1471-2202-3-1 Text en Copyright © 2002 Levine et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Methodology Article Levine, Joel D Funes, Pablo Dowse, Harold B Hall, Jeffrey C Signal analysis of behavioral and molecular cycles |
title | Signal analysis of behavioral and molecular cycles |
title_full | Signal analysis of behavioral and molecular cycles |
title_fullStr | Signal analysis of behavioral and molecular cycles |
title_full_unstemmed | Signal analysis of behavioral and molecular cycles |
title_short | Signal analysis of behavioral and molecular cycles |
title_sort | signal analysis of behavioral and molecular cycles |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC65508/ https://www.ncbi.nlm.nih.gov/pubmed/11825337 http://dx.doi.org/10.1186/1471-2202-3-1 |
work_keys_str_mv | AT levinejoeld signalanalysisofbehavioralandmolecularcycles AT funespablo signalanalysisofbehavioralandmolecularcycles AT dowseharoldb signalanalysisofbehavioralandmolecularcycles AT halljeffreyc signalanalysisofbehavioralandmolecularcycles |