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dc.contributor.authorEbrahimi, M.en
dc.contributor.authorEbrahimie, E.en
dc.contributor.authorEbrahimi, M.en
dc.contributor.authorDeihimi, T.en
dc.contributor.authorDelavari, A.en
dc.contributor.authorMohammadi-Dehcheshmeh, M.en
dc.identifier.citationIEEE Congress on Evolutionary Computation, 2009, CEC '09: pp.2885-2891en
dc.description.abstractThe 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 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.en
dc.description.statementofresponsibilityM. Ebrahimi, E. Ebrahimie, M. Ebrahimi, T. Deihimi, A. Delavari, M. Mohammadi-dehcheshmehen
dc.relation.ispartofseriesIEEE Congress on Evolutionary Computationen
dc.rights© 2009 IEEEen
dc.titleApplication of neural networks methods to define the most important features contributing to xylanase enzyme thermostabilityen
dc.typeConference paperen
dc.contributor.conferenceIEEE Congress on Evolutionary Computation (2009 : Trondheim, Norway)en
dc.identifier.orcidEbrahimie, E. [0000-0002-4431-2861]en
Appears in Collections:Animal and Veterinary Sciences publications
Aurora harvest 4

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