Promoter recognition for E. coli DNA segments by independent component analysis

Yasuo Matsuyama, Ryo Kawamura

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    Abstract

    A new method for E. coli DNA segment classification on promoters and non-promoters is presented. The algorithm is based on the Independent Component Analysis (ICA). Since the DNA segments are composed of discrete symbols, this paper contains two major steps: (1) Position-dependent transformation of DNA segments to real number sequences, and (2) Applications of the ICA to the E. coli promoter recognition. These steps are related to each other. Therefore, algorithmic explanations are given in detail while referring mutually. The automatic precision of 93.7% is obtained. Since the presented method allows threshold adjustments, twilight-zone data can be further cross-checked individually so that false negatives are reduced.

    Original languageEnglish
    Title of host publicationProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
    Pages686-691
    Number of pages6
    Publication statusPublished - 2004
    EventProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA
    Duration: 2004 Aug 162004 Aug 19

    Other

    OtherProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
    CityStanford, CA
    Period04/8/1604/8/19

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    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Matsuyama, Y., & Kawamura, R. (2004). Promoter recognition for E. coli DNA segments by independent component analysis. In Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 (pp. 686-691)