
Many biological processes are periodic, for example cell cycle expression, circadian rhythms and calcium oscillations. However, measured time series from these processes are commonly short and noisy, and finding frequencies in such data can be challenging. Here we present BaSAR, Bayesian Spectrum Analysis in R, a package for extracting frequency information from time series data. The software uses advanced techniques of Bayesian inference that are well suited for handling typical biological data. The core functions are designed for detecting a single key frequency, without the need for data pre-processing such as detrending. The package is freely available at CRAN - The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/BaSAR.
Statistics and Probability, Periodicity, Biochemistry, Genetics and Molecular Biology(all), Applied Mathematics, Statistics as Topic, R, Bayes Theorem, Frequency, Bayesian, Article, Modelling and Simulation, Software
Statistics and Probability, Periodicity, Biochemistry, Genetics and Molecular Biology(all), Applied Mathematics, Statistics as Topic, R, Bayes Theorem, Frequency, Bayesian, Article, Modelling and Simulation, Software
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
