• DocumentCode
    2535906
  • Title

    Robust entropy-enhanced frequency-domain genomic analysis under uncertainties

  • Author

    Lyshevski, Sergey Edward ; Krueger, Frank A.

  • Author_Institution
    Dept. of Electr. Eng., Rochester Inst. of Technol., NY, USA
  • fYear
    2004
  • fDate
    16-19 Aug. 2004
  • Firstpage
    556
  • Lastpage
    558
  • Abstract
    Here, we report the application of an entropy-enhanced frequency-domain analysis method to examine large-scale genomic data. This ensures superior coherency for qualitative and quantitative analysis. Different statistical methods are used to analyze large-scale data produced and attempts have been made to perform data mining. These efforts have been partially successful due to sequence gaps, noncoding and low complexity regions, inaccuracy, etc. In contrast, we report a novel robust method that is based on frequency-domain analysis. Our paradigm complements a number of far-reaching perceptions that new concepts emerge to comprehend complex large-scale genomic data under uncertainties.
  • Keywords
    data mining; frequency-domain analysis; genetics; maximum entropy methods; statistical analysis; complex large-scale genomic data; data mining; different statistical methods; robust entropy enhanced frequency-domain genomic analysis; sequence gaps; Bioinformatics; Data analysis; Data mining; Frequency domain analysis; Genomics; Large-scale systems; Performance analysis; Robustness; Statistical analysis; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nanotechnology, 2004. 4th IEEE Conference on
  • Print_ISBN
    0-7803-8536-5
  • Type

    conf

  • DOI
    10.1109/NANO.2004.1392418
  • Filename
    1392418