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
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