• DocumentCode
    1871040
  • Title

    Finding specific RNA sequence motifs using digital filters

  • Author

    Rajasekhar, K. ; Ahmad, M. Omair ; Devabhaktuni, Vijay

  • Author_Institution
    Electr. & Comput. Eng., Concordia Univ., Montreal, QC, Canada
  • fYear
    2012
  • fDate
    April 29 2012-May 2 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Local distinct structural elements, called motifs, in RNA sequences are strictly correlated with their function. Due to the enormous increase of genomic data in recent times, highly effective computational algorithms are in greater demand for identification of such motifs in RNA sequences. In this work, a digital signal processing approach using statistically optimal null filter (SONF) is developed for finding specific motifs in an RNA sequence. The instantaneous matched filter in SONF determines the degree of local alignment between the motif and the windowed RNA sequence being compared. Through example the effectiveness of the proposed approach is illustrated. In particular, the proposed method is highly efficient in identifying similar motifs in large RNA sequences.
  • Keywords
    RNA; biological techniques; digital filters; genomics; matched filters; molecular biophysics; signal processing; statistical analysis; RNA sequence motifs; digital filters; digital signal processing approach; genomic data; high effective computational algorithms; instantaneous matched filter; large RNA sequences; local alignment; local distinct structural elements; statistically optimal null filter; Bioinformatics; DNA; Genomics; Proteins; RNA; Signal to noise ratio; Ribonucleic acid (RNA); sequence motif; statistically optimal null filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Computer Engineering (CCECE), 2012 25th IEEE Canadian Conference on
  • Conference_Location
    Montreal, QC
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4673-1431-2
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2012.6335032
  • Filename
    6335032