• DocumentCode
    2088892
  • Title

    Cascaded Multi-level Promoter Recognition of  E. coli Using Dinucleotide Features

  • Author

    Rani, T. Sobha ; Bapi, Raju S.

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. of Hyderabad, Hyderabad, India
  • fYear
    2008
  • fDate
    17-20 Dec. 2008
  • Firstpage
    83
  • Lastpage
    88
  • Abstract
    Promoter recognition has been attempted using different paradigms such as motif/binding regions alone or whole promoter itself. In an earlier paper, a scheme is proposed to use 2-gram features to represent a promoter. These 2-grams gave a comparable performance with the existing methods in the literature. An in-depth analysis of data sets using 2-grams is performed. The analysis presented a scenario where there is a confusion between a majority of promoters with a minor set of non-promoter and vice versa. In an effort to build a complete classification system, using the majority and minority sets in promoters as well as non-promoters, a multi-level cascading system and Ada-Boost classifier are applied. The results indicate that much further improvement is not possible with the modifications proposed.
  • Keywords
    biology computing; data analysis; microorganisms; pattern classification; 2-gram features; Ada-Boost classifier; E. coli; cascaded multilevel promoter recognition; complete classification system; data analysis; data sets; dinucleotide features; in-depth analysis; majority sets; minority sets; motif/binding regions; multilevel cascading system; Computational intelligence; Data analysis; Feature extraction; Frequency; Gene expression; Information technology; Machine learning; Neural networks; Performance analysis; Switches; Ada-boost classifier; global feature extraction; machine learning techniques; neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology, 2008. ICIT '08. International Conference on
  • Conference_Location
    Bhubaneswar
  • Print_ISBN
    978-1-4244-3745-0
  • Type

    conf

  • DOI
    10.1109/ICIT.2008.56
  • Filename
    4731304