A full bayesian approach for boolean genetic network inference.

Boolean networks are a simple but efficient model for describing gene regulatory systems. A number of algorithms have been proposed to infer Boolean networks. However, these methods do not take full consideration of the effects of noise and model uncertainty.

Detection of dispersed short tandem repeats using reversible jump Markov chain Monte Carlo.

Tandem repeats occur frequently in biological sequences. They are important for studying genome evolution and human disease. A number of methods have been designed to detect a single tandem repeat in a sliding window.

An MCMC algorithm for detecting short adjacent repeats shared by multiple sequences.

Motivation: Repeats detection problems are traditionally formulated as string matching or signal processing problems. They cannot readily handle gaps between repeat units and are incapable of detecting repeat patterns shared by multiple sequences. This study detects short adjacent repeats with interunit insertions from multiple sequences.