• DocumentCode
    480630
  • Title

    UKF Based Self-Organizing Feature Maps Algorithm for the Recognition of Splice Sites

  • Author

    Su, Hongquan ; Zhu, Yi-Shen ; Zhang, Xiao-Hui

  • Author_Institution
    Inf. Coll., Dalian Maritime Univ., Dalian
  • Volume
    2
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    543
  • Lastpage
    547
  • Abstract
    Due to the higher dimensional and nonlinear properties of the gene sequences, traditional self-organizing feature maps can´t identify splice sites effectively. To circumvent the parameters study of the self-organizing feature maps, a method is presented based on the Kalman filter and the unscented transform which can identify splice sites effectively. By identifying the splice sites form long-scale and short-scale genomic DNA sequences, results show that the novel algorithm has competence.
  • Keywords
    DNA; Kalman filters; biology computing; genomics; self-organising feature maps; Kalman filter; UKF based self-organizing feature maps algorithm; gene sequences; genomic DNA sequences; splice sites recognition; unscented transform; Bioinformatics; DNA; Educational institutions; Filters; Genomics; Information technology; Jacobian matrices; Nearest neighbor searches; Neurons; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.367
  • Filename
    4739823