DocumentCode
2183402
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
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
5
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/BMEI.2009.5305127
Filename
5305127
Link To Document