Stochastic Complexity for the Detection of Periodically Expressed Genes

The problem we address in this study is to decide, based on the available measurements, if a particular gene exhibits a periodic behavior. To this end we propose a principled method relying on the Stochastic Complexity (SC) whose computation is discussed for the generalized Gaussian distribution. We also investigate the relationship between SC, the well-known Minimum Description Length (MDL) formula, and the Bayesian Information Criterion (BIC). The performances of the SC-based approach are compared for simulated and real data with methods that are widely accepted in the bioinformatics community.