Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data

@article{Hoon2004PredictingGR,
  title={Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data},
  author={Michiel J. L. de Hoon and Yuko Makita and Seiya Imoto and Kazuo Kobayashi and Naotake Ogasawara and Kenta Nakai and Satoru Miyano},
  journal={Bioinformatics},
  year={2004},
  volume={20 Suppl 1},
  pages={i101-8}
}
MOTIVATION Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. We assess the accuracy of a fold-change analysis, Bayesian networks, dynamic models and supervised learning based on coregulation in predicting gene regulation by sigma factors from gene expression data. To improve the prediction accuracy, we combine sequence information with expression data by adding their log-likelihood scores and by using a logistic regression model. We use the… CONTINUE READING
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