Center for Computational Biology, Indraprastha Institute of Information Technology Delhi, New Delhi 110020, India.
IET Syst Biol. 2019 Aug;13(4):159-168. doi: 10.1049/iet-syb.2018.5088.
In this work, the authors propose the Hilbert transform (HT)-based numerical method to analyse the time series of the circadian rhythms. They demonstrate the application of HT by taking both deterministic and stochastic time series that they get from the simulation of the fruit fly model and show how to extract the period, construct phase response curves, determine period sensitivity of the parameters to perturbations and build Arnold tongues to identify the regions of entrainment. They also derive a phase model that they numerically simulate to capture whether the circadian time series entrains to the forcing period completely (phase locking) or only partially (phase slips) or neither. They validate the phase model, and numerics with the experimental time series forced under different temperature cycles. Application of HT to the circadian time series appears to be a promising tool to extract the characteristic information about circadian rhythms.
在这项工作中,作者提出了基于希尔伯特变换(HT)的数值方法来分析昼夜节律的时间序列。他们通过使用从果蝇模型的模拟中得到的确定性和随机性时间序列来展示 HT 的应用,并展示如何提取周期、构建相位响应曲线、确定参数对扰动的周期敏感性以及构建 Arnold 音来识别同步区域。他们还推导出一个相位模型,通过数值模拟来捕捉昼夜时间序列是否完全(相位锁定)或仅部分(相位滑动)或都不锁定到强迫周期。他们通过在不同温度循环下对实验时间序列进行强迫来验证相位模型和数值。将 HT 应用于昼夜时间序列似乎是一种很有前途的工具,可以提取关于昼夜节律的特征信息。