Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/83797
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Type: Conference paper
Title: Application of neural networks methods to define the most important features contributing to xylanase enzyme thermostability
Author: Ebrahimi, M.
Ebrahimie, E.
Ebrahimi, M.
Deihimi, T.
Delavari, A.
Mohammadi-Dehcheshmeh, M.
Citation: IEEE Congress on Evolutionary Computation, 2009, CEC '09: pp.2885-2891
Publisher: IEEE
Publisher Place: USA
Issue Date: 2009
Series/Report no.: IEEE Congress on Evolutionary Computation
ISBN: 9781424429585
Conference Name: IEEE Congress on Evolutionary Computation (2009 : Trondheim, Norway)
Statement of
Responsibility: 
M. Ebrahimi, E. Ebrahimie, M. Ebrahimi, T. Deihimi, A. Delavari, M. Mohammadi-dehcheshmeh
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.
Rights: © 2009 IEEE
DOI: 10.1109/CEC.2009.4983305
Appears in Collections:Animal and Veterinary Sciences publications
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