• DocumentCode
    508060
  • Title

    StSUT2 Structure Prediction Based on Nucleic Acid Sequence Using GA-BP

  • Author

    Zhu, Zhengwei ; Guo, Yuying

  • Author_Institution
    Sch. of Inf. Eng., Southwest Univ. of Sci. & Technol., Mianyang, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    149
  • Lastpage
    153
  • Abstract
    The protein secondary structure (PSS) prediction system presented in this paper is a subsystem of potato bioinformation research platform. The proposed method is a novel and practical PSS prediction method, which is based on nucleic acid sequence (NAS), uses an combined neural network (CNN) and takes an improved genetic algorithm (GA) to optimize the connection weights of CNN. The experimental results indicate that, not only the proposed method is feasible, but compared with the traditional PSS prediction methods, its prediction accuracy is higher, its use is more convenient, its search speed is faster and it has confidentiality in a certain degree.
  • Keywords
    bioinformatics; genetic algorithms; macromolecules; neural nets; proteins; StSUT2 structure prediction; combined neural network; genetic algorithm; nucleic acid sequence; potato bioinformation research; protein secondary structure; Accuracy; Amino acids; Cellular neural networks; Genetic mutations; Neural networks; Neurons; Optimization methods; Prediction methods; Predictive models; Proteins; Potato; combined neural network; improved genetic algorithm; nucleic acid sequence; protein structure prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.172
  • Filename
    5365202