DocumentCode
2380676
Title
MiRPara: A SVM-based software for prediction of mature miRNAs
Author
Wu, Yonggan ; Wei, Bo ; Liu, Haizhou ; Han, Na ; Rayner, Simon
Author_Institution
State Key Lab. of Virology, Chinese Acad. of Sci., Wuhan, China
fYear
2010
fDate
18-18 Dec. 2010
Firstpage
839
Lastpage
840
Abstract
miRPara, is a new software tool that predicts mature miRNA in a species specific manner based on three SVM trained models from a comprehensive set of different parameters related to the physical properties of the pre-miRNA and its miRNAs. It achieves an accuracy of up to 80% for animal and virus sequences against experimentally verified mature miRNAs predicted from long genome sequences, making it one of the most accurate methods available. Because of the greater diversity of the plant miRNAs, only 70% accuracy was achieved, but this was nevertheless more accurate than results obtained with other prediction software.
Keywords
bioinformatics; genomics; macromolecules; molecular biophysics; organic compounds; software tools; support vector machines; SVM trained model; SVM-based software; animal sequences; long genome sequences; mature miRNA prediction; miRPara; software tool; virus sequences; SVM; component; formatting; miRNA; predict;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
Conference_Location
Hong, Kong
Print_ISBN
978-1-4244-8303-7
Electronic_ISBN
978-1-4244-8304-4
Type
conf
DOI
10.1109/BIBMW.2010.5703935
Filename
5703935
Link To Document