A Bayesian Network Approach to Operon Prediction

  title={A Bayesian Network Approach to Operon Prediction},
  author={Joseph Bockhorst and Mark Craven and David Page and Jude W. Shavlik and Jeremy D. Glasner},
  volume={19 10},
MOTIVATION In order to understand transcription regulation in a given prokaryotic genome, it is critical to identify operons, the fundamental units of transcription, in such species. While there are a growing number of organisms whose sequence and gene coordinates are known, by and large their operons are not known. RESULTS We present a probabilistic approach to predicting operons using Bayesian networks. Our approach exploits diverse evidence sources such as sequence and expression data. We… CONTINUE READING
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