• DocumentCode
    2289913
  • Title

    RNA secondary structure prediction algorithm based on combinatorial optimization algorithm and SVMs method

  • Author

    He Jing-yuan ; Mu Chao ; Huang Hai-hun

  • Author_Institution
    Coll. of Comput. Sci., Chongqing Univ., Chongqing, China
  • fYear
    2012
  • fDate
    6-8 July 2012
  • Firstpage
    715
  • Lastpage
    719
  • Abstract
    A new RNA secondary structure prediction algorithm that can predict pseudoknots is proposed, it combines the stem-loop combinatorial optimization algorithm and SVMs(Support Vector Machines, SVMs) method. The algorithm firstly finds out the optimal stem-loop structure and suboptimum structures based on dynamic neighbor topology particle swarm optimization algorithm, and then puts these loops into SVMs. The output from SVMs can decide whether there exist a pseudoknot. The experimental results demonstrate the superiority of our algorithm over the other methods in terms of solution quality and convergence rates.
  • Keywords
    RNA; biology computing; cellular biophysics; particle swarm optimisation; support vector machines; RNA secondary structure prediction; SVM method; convergence rates; dynamic neighbor topology particle swarm optimization; optimal stem-loop structure; pseudoknots; solution quality; stem-loop combinatorial optimization; suboptimum structures; support vector machines; Classification algorithms; Convergence; Heuristic algorithms; Optimization; Prediction algorithms; RNA; Topology; RNA secondary structure prediction; SVMs; dynamic neighbor topology; particle optimization algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2012 10th World Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-1397-1
  • Type

    conf

  • DOI
    10.1109/WCICA.2012.6357971
  • Filename
    6357971