• DocumentCode
    3238953
  • Title

    Inferring transmembrane region counts with hydropathy index/charge two dimensional trajectories of stochastic dynamical systems

  • Author

    Muramatsu, D. ; Hashimoto, S. ; Tsunashima, T. ; Kaburagi, T. ; Sasaki, M. ; Matsumoto, T.

  • Author_Institution
    Dept. of Electr. Eng. & Bioscience, Waseda Univ., Tokyo, Japan
  • fYear
    2003
  • fDate
    17-19 Sept. 2003
  • Firstpage
    101
  • Lastpage
    110
  • Abstract
    A new algorithm is proposed for inferring the number of transmembrane regions of transmembrane proteins from two dimensional vector trajectories consisting of hydropathy index and charge of amino acids by stochastic dynamical system models. The prediction accuracy of a preliminary experiment is 94%. Since no fine-tuning is done, this appears encouraging.
  • Keywords
    biomembranes; molecular biophysics; proteins; stochastic systems; amino acids; hydropathy charge; hydropathy index; stochastic dynamical systems; transmembrane proteins; transmembrane region counts; vector trajectories; Accuracy; Amino acids; Biomembranes; Data mining; Equations; Feature extraction; Hidden Markov models; Machine learning algorithms; Protein engineering; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing, 2003. NNSP'03. 2003 IEEE 13th Workshop on
  • ISSN
    1089-3555
  • Print_ISBN
    0-7803-8177-7
  • Type

    conf

  • DOI
    10.1109/NNSP.2003.1318008
  • Filename
    1318008