Abstract
Abstract: Circadian clocks permit mammals to adapt to their periodic natural environment. These clocks generate rhythms in the expression of genes and proteins in most tissues within the organism. Real-time bioluminescence recordings of gene or protein expression in an important tool to study the clock under different manipulations and conditions. Here, we present a tool to extract useful characteristics of the cellular rhythms, such as period and damping rate, using maximum-likelihood estimation in a stochastic damped oscillator model. The tool uses the expectation-maximization algorithm in combination with a Kalman Smoother to perform the joint state and parameter estimation. We apply this tool to quantify the differences between rhythms in the master circadian clock in the brains of two different knockout mice and compare the results to a standard autocovariance fitting-based approach for parameter estimation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
