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Predicting Enzyme Subclasses by Using Support Vector Machine with Composite Vectors

[ Vol. 17 , Issue. 5 ]

Author(s):

Ruijia Shi and Xiuzhen Hu   Pages 599 - 604 ( 6 )

Abstract:


Based on enzyme sequence, using composite vectors with amino acid composition, low-frequency power spectral density, increment of diversity by combining a different form of pseudo amino acid composition to express the information of sequence, a support vector machine (SVM) for predicting enzyme subclasses is proposed. By the jackknife test, success rates of our algorithm are higher than other methods.

Keywords:

Enzymes, enzyme subclasses, low-frequency power spectral density, pseudo amino acid composition, increment of diversity, support vector machine, jackknife test

Affiliation:

College of Sciences, Inner Mongolia University of Technology, Hohhot, 010051, China.



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