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Predicting enzyme subclasses by using random forest with multicharacteristic parameters
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نویسنده
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wang y. ,hu x. ,sun l. ,feng z. ,song h.
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منبع
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protein and peptide letters - 2014 - دوره : 21 - شماره : 3 - صفحه:275 -284
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چکیده
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In order to predict enzyme subclasses,this paper builds a new enzyme database in term of previous ideas and methods. based on protein sequence,by selecting increment of diversity value,low-frequency of power spectral density,matrix scoring values and motif frequency as characteristic parameters to describe the sequence information,a random forest algorithm for predicting enzyme subclass is proposed. using the jack-knife test,the overall success rate identifying the 18 subclasses of oxidoreductases,the 8 subclasses of transferases,the 5 subclasses of hydrolases,the 6 subclasses of lyases,the 6 subclasses of isomerases,and the 6 subclasses of ligases are 90.86%,95.24%,96.42%,98.60%,97.53% and 98.03%. furthermore,the same way is used to the previous database,the better results are obtained. © 2014 bentham science publishers.
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کلیدواژه
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Enzyme subclasses; Increment of diversity value; Matrix scoring function value; Motif; Prediction; Random forest algorithm
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آدرس
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college of sciences,inner mongolia university of technology,hohhot,010051,china,qiqihar institute of technology,qiqihar, China, college of sciences,inner mongolia university of technology,hohhot, China, college of sciences,inner mongolia university of technology,hohhot, China, college of sciences,inner mongolia university of technology,hohhot, China, college of sciences,inner mongolia university of technology,hohhot, China
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Authors
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