• DocumentCode
    1642737
  • Title

    Application of neural networks methods to define the most important features contributing to xylanase enzyme thermostability

  • Author

    Ebrahimi, Mojtaba ; Ebrahimie, E. ; Ebrahimi, Mojtaba ; Deihimi, T. ; Delavari, A. ; Mohammadi-dehcheshmeh, M.

  • Author_Institution
    Green Res. Center, Qom Univ., Qom
  • fYear
    2009
  • Firstpage
    2885
  • Lastpage
    2891
  • Abstract
    The importance of finding or making thermostable enzymes in different industries have been highlighted. Therefore, it is inevitable to understand the features involving in enzymes´ thermostability. Different approaches have been employed to extract or manufacture thermostable enzymes. Here we have looked at features contributing to Endo-1,4,beta-xylanase (EC 3.2.1.8) thermostability, the key enzyme with possible applications in waste treatment, fuel and chemical production and paper industries. We trained different neural networks with/without feature selection and classification modelling on all available xylanase enzymes amino acids sequences to find features contributing to enzyme thermal stability.
  • Keywords
    biology computing; enzymes; macromolecules; neural nets; thermal stability; Bacillus halodurans mutants; Endo-1,4,beta-xylanase; Lys Frequency; Met Frequency; classification modelling; dynamic method; feature selection; multiple model; neural networks methods; xylanase enzyme thermostability; Amino acids; Biochemistry; Chemical industry; Chemical products; Fuels; Manufacturing industries; Neural networks; Production; Pulp and paper industry; Thermal stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983305
  • Filename
    4983305