• DocumentCode
    3391007
  • Title

    Multifractal analysis and feature extraction of DNA sequences

  • Author

    Kinsner, Witold ; Zhang, Hong

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB, Canada
  • fYear
    2009
  • fDate
    15-17 June 2009
  • Firstpage
    29
  • Lastpage
    37
  • Abstract
    This paper presents feature extraction and estimations of multifractal measures for deoxyribonucleic acid (DNA) sequences, and demonstrates the intriguing possibility of identifying biological functionality using information contained within the DNA sequence. We have developed a technique that seeks patterns or correlations in the DNA sequence at a higher level. The technique has three main steps: (i) transforms the DNA sequence symbols into a modified Levy walk, (ii) transforms the Levy walk into a signal spectrum, and (iii) breaks the spectrum into subspectra and treats each of these as an attractor from which the multifractal dimension spectrum is estimated. An optimal minimum window size and volume element size are found for estimation of the multifractal measures. Experimental results show that DNA is a multifractal, and that the multifractality changes depending upon the location (coding or noncoding region) in the sequence.
  • Keywords
    DNA; feature extraction; image sequences; medical image processing; DNA sequences; Levy walk; biological functionality; deoxyribonucleic acid; feature extraction; multifractal analysis; optimal minimum window size; signal spectrum; DNA; Feature extraction; Fractals; Sequences; DNA sequences; feature extraction for classification; multifractal analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
  • Conference_Location
    Kowloon, Hong Kong
  • Print_ISBN
    978-1-4244-4642-1
  • Type

    conf

  • DOI
    10.1109/COGINF.2009.5250696
  • Filename
    5250696