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
Link To Document :
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