• DocumentCode
    2528291
  • Title

    On discriminating a TATA-box from putative TATA boxes: a case study using plant genome

  • Author

    Loganantharaj, Raja

  • Author_Institution
    Bioinformatics Res. Lab., Univ. of Louisiana, Lafayette, LA, USA
  • fYear
    2005
  • fDate
    8-11 Aug. 2005
  • Firstpage
    201
  • Lastpage
    202
  • Abstract
    Prediction of a promoter is one of the many active areas of bioinformatics. The outcome of a promoter detection algorithm is directly or indirectly influenced by the success of identifying the location of a TATA box in a promoter sequence. A profiling technique is very often used to find putative TATA boxes, but discriminating a TATA box from putative TATA boxes is still a challenging problem. In this work, we formulate the problem and provide solutions using both a linear and a non linear classifiers.
  • Keywords
    biology computing; neural nets; artificial neural network; bioinformatics; nonlinear classifiers; profiling technique; promoter detection algorithm; promoter sequence; putative TATA box; Accuracy; Artificial neural networks; Bioinformatics; Computer aided software engineering; Databases; Detection algorithms; Genomics; Neural networks; Prediction algorithms; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE
  • Print_ISBN
    0-7695-2442-7
  • Type

    conf

  • DOI
    10.1109/CSBW.2005.99
  • Filename
    1540598