• DocumentCode
    2234357
  • Title

    An AdaBoost Algorithm for the Identification of Arabidopsis Messenger RNA Polyadenylation Sites

  • Author

    Ji, Guoli ; Zou, Dan ; Zheng, Jianti ; Li, Qingshun Quinn

  • Author_Institution
    Dept. of Autom., Xiamen Univ., Xiamen, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    3579
  • Lastpage
    3582
  • Abstract
    To predict messenger RNA poly (A) sites of model plant Arabidopsis, we present a solution based on the AdaBoost (Adaptive Boosting) algorithm. Through the analysis of experimental results and comparing with the results produced by Support Vector Machine, with the progressive reduction of the training sample sizes, we still can get satisfying stable comprehensive evaluation index. This demonstrates the effectiveness of the method in identification of poly (A) sites.
  • Keywords
    chemistry computing; macromolecules; support vector machines; AdaBoost algorithm; adaptive boosting; arabidopsis messenger RNA polyadenylation sites; support vector machine; Bioinformatics; Boosting; Gene expression; Humans; Information science; Machine learning; Machine learning algorithms; RNA; Sequences; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.224
  • Filename
    5455597