• DocumentCode
    3355338
  • Title

    Prediction of Transmembrane Helical Segments in Membrane Proteins Using Back Propagation Neural Network with Wavelet Analysis

  • Author

    Yu Bin

  • Author_Institution
    Coll. of Math. & Phys., Qingdao Univ. of Sci. & Technol., Qingdao, China
  • Volume
    2
  • fYear
    2009
  • fDate
    28-30 Oct. 2009
  • Firstpage
    563
  • Lastpage
    567
  • Abstract
    Transmembrane proteins possess important physiological function. The increasing transmembrane protein sequences from genome projects raise the needs for theoretical methods to predict their structures, especially transmembrane helical segments (TMHs). wnnTM, a new method of BP neural network based on wavelet multiresolution analysis (MRA) is initially developed to predict the number and location of TMHs in membrane proteins. 80 proteins with known 3D-structure randomly selected from Mptopo database are used as test set to evaluate the prediction accuracy of the method. The final results indicate that the proposed method is more effective than BP neural network model only.
  • Keywords
    backpropagation; bioinformatics; biomembranes; neural nets; proteins; Mptopo database; backpropagation neural network; genome sequences; transmembrane helical segments prediction; transmembrane protein sequences; wavelet multiresolution analysis; Accuracy; Bioinformatics; Biomembranes; Databases; Genomics; Multiresolution analysis; Neural networks; Protein engineering; Testing; Wavelet analysis; BP neural network; membrane protein; transmembrane helical segments; wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-0-7695-3881-5
  • Type

    conf

  • DOI
    10.1109/WCSE.2009.876
  • Filename
    5403518