A Full Bayesian Approach for Boolean Genetic Network Inference

@inproceedings{Han2014AFB,
  title={A Full Bayesian Approach for Boolean Genetic Network Inference},
  author={Shengtong Han and Raymond K. W. Wong and Thomas C. M. Lee and Linghao Shen and Shuo-Yen Robert Li and Xiaodan Fan},
  booktitle={PloS one},
  year={2014}
}
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. In this paper, we propose a full Bayesian approach to infer Boolean genetic networks. Markov chain Monte Carlo algorithms are used to obtain the posterior samples of both the network structure and the related parameters. In addition to… CONTINUE READING