Departamento de Fisiologia e Biofísica, Instituto de Ciências Biológicas - Universidade Federal de Minas Gerais, Belo Horizonte, Brasil; Centro de Tecnologia e Pesquisa em Magneto Ressonância, Programa de Pós-Graduação em Engenharia Elétrica - Universidade Federal de Minas Gerais, Belo Horizonte, Brasil.
Departamento de Fisiologia e Biofísica, Instituto de Ciências Biológicas - Universidade Federal de Minas Gerais, Belo Horizonte, Brasil.
J Neurosci Methods. 2024 Nov;411:110245. doi: 10.1016/j.jneumeth.2024.110245. Epub 2024 Aug 6.
Chronobiology is the scientific field focused on studying periodicity in biological processes. In mammals, most physiological variables exhibit circadian rhythmicity, such as metabolism, body temperature, locomotor activity, and sleep. The biological rhythmicity can be statistically evaluated by examining the time series and extracting parameters that correlate to the period of oscillation, its amplitude, phase displacement, and overall variability.
We have developed a library called CircadiPy, which encapsulates methods for chronobiological analysis and data inspection, serving as an open-access toolkit for the analysis and interpretation of chronobiological data. The package was designed to be flexible, comprehensive and scalable in order to assist research dealing with processes affected or influenced by rhythmicity.
The results demonstrate the toolkit's capability to guide users in analyzing chronobiological data collected from various recording sources, while also providing precise parameters related to the circadian rhythmicity.
The analysis methodology from this proposed library offers an opportunity to inspect and obtain chronobiological parameters in a straightforward and cost-free manner, in contrast to commercial tools.
Moreover, being an open-source tool, it empowers the community with the opportunity to contribute with new functions, analysis methods, and graphical visualizations given the simplified computational method of time series data analysis using an easy and comprehensive pipeline within a single Python object.
时间生物学是专注于研究生物过程周期性的科学领域。在哺乳动物中，大多数生理变量表现出昼夜节律性，如代谢、体温、活动和睡眠。生物节律性可以通过检查时间序列并提取与振荡周期、振幅、相位偏移和整体可变性相关的参数来进行统计评估。
我们开发了一个名为 CircadiPy 的库，它封装了用于时间生物学分析和数据检查的方法，是分析和解释时间生物学数据的开放工具包。该软件包旨在具有灵活性、全面性和可扩展性，以帮助研究受节律性影响或影响的过程。
结果表明，该工具包能够指导用户分析从各种记录源收集的时间生物学数据，同时还提供与昼夜节律性相关的精确参数。
与商业工具相比，该库的分析方法提供了一种直接且免费的方式来检查和获取时间生物学参数的机会。
此外，作为一个开源工具，它使社区有机会通过使用简化的时间序列数据分析计算方法，在单个 Python 对象中使用简单而全面的管道，为新功能、分析方法和图形可视化提供贡献。
