• DocumentCode
    677359
  • Title

    Approximation algorithm of the RNA pseudoknotted structure prediction baesed on MFE

  • Author

    Zhendong Liu ; Yuejun Li ; Peng Zhang ; Zhaohui Yang

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Shandong Jianzhu Univ., Jinan, China
  • fYear
    2013
  • fDate
    26-28 Aug. 2013
  • Firstpage
    1045
  • Lastpage
    1049
  • Abstract
    Determination of Ribonucleic Acid structure is challenging, in order to optimize the RNA pseudoknotted structure,the paper investigates the computational problem and complexity of predicting RNA structure. A new computational method and model with minimum free energy are adopted to predict RNA structure. The main contribution of the paper is to achieves an efficient approximation algorithm for finding RNA pseudoknotted structure and nested structures. We have compared with other algorithms in time complexity and space complexity, the approximation algorithm takes O(n3) time and O(n2) space,where n is the length of the RNA sequences. The experimental tests for a large database of RNA show that the algorithm is more exact and effective than the algorithms, the algorithm can predict arbitrary pseudoknots, and improve the a predicting accuracy.
  • Keywords
    RNA; approximation theory; biology computing; computational complexity; optimisation; MFE; RNA pseudoknotted structure optimisation; RNA pseudoknotted structure prediction; RNA sequences; RNA structure prediction complexity; approximation algorithm; minimum free energy; nested structures; ribonucleic acid structure determination; space complexity; time complexity; Algorithm design and analysis; Approximation algorithms; Approximation methods; Heuristic algorithms; Prediction algorithms; RNA; Time complexity; Approximation algorithm; Minimum free energy; RNA Pseudoknotted structure; Stacking pairs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2013 IEEE International Conference on
  • Conference_Location
    Yinchuan
  • Type

    conf

  • DOI
    10.1109/ICInfA.2013.6720449
  • Filename
    6720449