• DocumentCode
    2550576
  • Title

    Protein Secondary Structure Prediction based on BP Neural Network and Quasi-Newton Algorithm

  • Author

    Wang, Jian ; Li, Jian-Ping

  • Author_Institution
    Sch. of Comput. & Inf. Sci., Neijiang Normal Univ., Neijiang
  • fYear
    2008
  • fDate
    13-15 Dec. 2008
  • Firstpage
    128
  • Lastpage
    131
  • Abstract
    Based on neural network, an improvement scheme that iterative matrix replace secondary derivative has been developed by introduced quasi-Newton algorithm. Profile code based on probability has been used and comparison of window width and learning training has been completed. The experiment results indicate that the prediction for secondary structures of protein obtain a very good effect based on neural network and quasi-Newton algorithm.
  • Keywords
    backpropagation; biology computing; iterative methods; matrix algebra; neural nets; BP neural network; iterative matrix; protein secondary structure prediction; quasi-Newton algorithm; Accuracy; Amino acids; Convergence; Databases; Iterative algorithms; Neural networks; Neurons; Potential well; Prediction methods; Proteins; BP neural network; Quasi-Newton algorithm; prediction; protein secondary structure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Apperceiving Computing and Intelligence Analysis, 2008. ICACIA 2008. International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-3427-5
  • Electronic_ISBN
    978-1-4244-3426-8
  • Type

    conf

  • DOI
    10.1109/ICACIA.2008.4769988
  • Filename
    4769988
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2550576