Chronobiology is the study of biological timing. Life unfolds within the context of time, with one of the most apparent measures of time being the 24-hour day-night cycle. Our internal biological rhythm, known as circadian rhythm, which is almost 24 hours long, is fascinatingly dependent on the external 24-hour day-night cycle to coordinate daily biological functions. As scientists advance the field of chronobiology, accessible methods that deliver quality results are essential for maximizing impact and ensuring widespread applicability.
This Methods Collection aims to highlight recent strategies for studying the timing of biological processes. Techniques highlighting the significance of modulatory environmental factors, such as the day-night cycle, are encouraged. Molecular, in vitro, in vivo, behavioral, physiological, and electrophysiological methods are also welcome. These approaches should address fundamental questions in chronobiology and be designed for easy translation and reproducibility. If the methodology involves a specialized tool, it must be readily accessible for others to adopt or purchase. By offering a comprehensive collection of cutting-edge methods and fostering collaboration among researchers, this initiative will accelerate progress in chronobiology.
0 Views
•
2026
•
Bárbara Ramalho1,2, Cristiana Fernandes1,2, Bárbara Santos1,2,3, Laetitia S. Gaspar1,2,4, Rodrigo F. N. Ribeiro1,2,3,4, Cláudia Cavadas1,2,3,4, Ana Capitão1,2, Ana Rita Álvaro1,2,5
1CNC-UC-Center for Neuroscience and Cell Biology, University of Coimbra, 2CiBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3Faculty of Pharmacy, University of Coimbra, 4Gene Therapy Center of Excellence (GeneT), University of Coimbra, 5Institute for Interdisciplinary Research (IIIUC), University of Coimbra
An Open-source platform for the non-stationary for circadian rhythm analysis using Wavelet transforms
Eddie Perez Claudio*1,
Jonathan Aleman-Rios2,
Jose Agosto-Rivera2,
Manuel Giannoni Guzman*3
1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States,
2Department of Biology, University of Puerto Rico Rio Piedras, San Juan, Puerto Rico, United States,
3Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States
Analyzing sleep and circadian rhythm data
Elizabeth Klerman*1
1Massachusetts General Hospital, Harvard Medical School