Title :
Prediction of Membrane Protein Types by Using Support Vector Machine Based on Composite Vector
Author :
Wang, Ting ; Hu, Xiu Zhen
Author_Institution :
Coll. of Sci., Inner Mongolia Univ. of Technol., Hohhot, China
Abstract :
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.
Keywords :
biomembranes; proteins; support vector machines; composite vector; membrane protein type prediction; support vector machine; Amino acids; Bioinformatics; Biomembranes; Cells (biology); Educational institutions; Genomics; Humans; Prediction algorithms; Protein engineering; Support vector machines;
Conference_Titel :
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4132-7
Electronic_ISBN :
978-1-4244-4134-1
DOI :
10.1109/BMEI.2009.5305127
