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• W2011082170 abstract "In this paper we intend to apply a new method to predict tertiary structure. Several feature extraction methods adopted are physicochemical composition, recurrence quantification analysis (RQA) , pseudo amino acid composition (PseAA) and Distance frequency. We construct the binary tree Classification model, and adopt flexible neural tree models as the classifiers. We will train a number of based classifiers through different features extraction methods for every node of binary tree, then employ the selective ensemble method to ensemble them. 640 dataset is selected to our experiment. The predict accuracy with our method on this data set is 63.58%, higher than some other methods on the 640 datasets. So, our method is feasible and effective in some extent." @default.
• W2011082170 created "2016-06-24" @default.
• W2011082170 creator A5022005700 @default.
• W2011082170 creator A5036677646 @default.
• W2011082170 date "2013-09-01" @default.
• W2011082170 modified "2023-09-25" @default.
• W2011082170 title "Predict the Tertiary Structure of Protein with Binary Tree and Ensemble Strategy" @default.
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• W2011082170 doi "https://doi.org/10.4028/www.scientific.net/amr.765-767.3081" @default.
• W2011082170 hasPublicationYear "2013" @default.
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