• DocumentCode
    501094
  • Title

    Statistical Study on Disease-Related ncRNAs Using Z-curve Method

  • Author

    Yang, Yan-ling

  • Author_Institution
    Key Lab. for Biophys., Universities of Shandong, De Zhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    503
  • Lastpage
    506
  • Abstract
    It has become very important to study non-coding RNAs in the recent years. The Z curve is a very useful method for visualizing and analyzing DNA sequences among the approaches of researching ncRNAs. It is a three-dimensional space curve that constitutes a unique representation of a given DNA sequence, i.e., both the Z-curve and the given DNA sequence can be uniquely reconstructed from the other. Using Z curve method, we select 15 disease related ncRNAs sequences from the NONCODE database, which relate with Alzheimer Disease. The corresponding Z curves of the studied ncRNAs, sequences have been mapped and compared. The statistical features of the Z curves are obtained. These features indicate that the ncRNAs sequences, which play same roles in the cellular process, have almost the same Z-curves. And the base content in these sequences is almost same too, in spite of coming from different organisms.
  • Keywords
    DNA; cellular biophysics; diseases; feature extraction; medical computing; medical information systems; statistical analysis; 3D space curve; Alzheimer disease; NONCODE database; Z curve statistical feature; Z-curve reconstruction; cellular process; disease-related ncRNA sequence; noncoding RNA; unique DNA sequence representation; Alzheimer´s disease; Bioinformatics; Cardiac disease; Cardiovascular diseases; DNA; Degenerative diseases; Genomics; Organisms; RNA; Sequences; Alzheimer Disease; NONCODE; Z-curve; base content; ncRNA; non-coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.80
  • Filename
    5231071