Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint

Anders Gorm Pedersen, Jacob Engelbrecht

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    We present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced along the promoter region. The spacing of all signals correspond to the helical periodicity of DNA, meaning that the signals are all present on the same face of the DNA helix in the promoter region. This is consistent with a model where the RNA polymerase contacts the promoter on one side of the DNA, and suggests that the regions important for promoter recognition may include more positions on the DNA than usually assumed. We furthermore analyze the E. coli promoters by calculating the Kullback Leibler distance, and by constructing sequence logos.
    Original languageEnglish
    Title of host publicationISMB-95 Proceedings : Proceedings Third International Conference on Intelligent Systems for Molecular Biology
    PublisherAAAI Press
    Publication date1995
    Pages292-299
    ISBN (Print)0929280830
    Publication statusPublished - 1995

    Cite this

    Pedersen, A. G., & Engelbrecht, J. (1995). Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint. In ISMB-95 Proceedings: Proceedings Third International Conference on Intelligent Systems for Molecular Biology (pp. 292-299). AAAI Press.
    Pedersen, Anders Gorm ; Engelbrecht, Jacob. / Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint. ISMB-95 Proceedings: Proceedings Third International Conference on Intelligent Systems for Molecular Biology. AAAI Press, 1995. pp. 292-299
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    abstract = "We present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced along the promoter region. The spacing of all signals correspond to the helical periodicity of DNA, meaning that the signals are all present on the same face of the DNA helix in the promoter region. This is consistent with a model where the RNA polymerase contacts the promoter on one side of the DNA, and suggests that the regions important for promoter recognition may include more positions on the DNA than usually assumed. We furthermore analyze the E. coli promoters by calculating the Kullback Leibler distance, and by constructing sequence logos.",
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    Pedersen, AG & Engelbrecht, J 1995, Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint. in ISMB-95 Proceedings: Proceedings Third International Conference on Intelligent Systems for Molecular Biology. AAAI Press, pp. 292-299.

    Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint. / Pedersen, Anders Gorm; Engelbrecht, Jacob.

    ISMB-95 Proceedings: Proceedings Third International Conference on Intelligent Systems for Molecular Biology. AAAI Press, 1995. p. 292-299.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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    AB - We present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced along the promoter region. The spacing of all signals correspond to the helical periodicity of DNA, meaning that the signals are all present on the same face of the DNA helix in the promoter region. This is consistent with a model where the RNA polymerase contacts the promoter on one side of the DNA, and suggests that the regions important for promoter recognition may include more positions on the DNA than usually assumed. We furthermore analyze the E. coli promoters by calculating the Kullback Leibler distance, and by constructing sequence logos.

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    Pedersen AG, Engelbrecht J. Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint. In ISMB-95 Proceedings: Proceedings Third International Conference on Intelligent Systems for Molecular Biology. AAAI Press. 1995. p. 292-299