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Prediction of Membrane Protein Types by Using Support Vector Machine Based on Composite Vector

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2 Author(s)
Ting Wang ; Coll. of Sci., Inner Mongolia Univ. of Technol., Hohhot, China ; Xiu Zhen Hu

By using of the composite vector with increment of diversity and scoring function to express the information of sequence, a support vector machine (SVM) algorithm for predicting the eight types of membrane proteins is proposed. The overall jackknife success rate is 91.81% what is higher than other results. In order to evaluate the predictive method, the six types of membrane proteins are predicted by using our method. The better results are obtained.

Published in:
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on

Date of Conference: 17-19 Oct. 2009

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