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|Title:||Application of neural networks methods to define the most important features contributing to xylanase enzyme thermostability|
|Citation:||IEEE Congress on Evolutionary Computation, 2009, CEC '09: pp.2885-2891|
|Series/Report no.:||IEEE Congress on Evolutionary Computation|
|Conference Name:||IEEE Congress on Evolutionary Computation (2009 : Trondheim, Norway)|
|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 22.214.171.124) 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|
|Appears in Collections:||Animal and Veterinary Sciences publications|
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