Title :
An AdaBoost Algorithm for the Identification of Arabidopsis Messenger RNA Polyadenylation Sites
Author :
Ji, Guoli ; Zou, Dan ; Zheng, Jianti ; Li, Qingshun Quinn
Author_Institution :
Dept. of Autom., Xiamen Univ., Xiamen, China
Abstract :
To predict messenger RNA poly (A) sites of model plant Arabidopsis, we present a solution based on the AdaBoost (Adaptive Boosting) algorithm. Through the analysis of experimental results and comparing with the results produced by Support Vector Machine, with the progressive reduction of the training sample sizes, we still can get satisfying stable comprehensive evaluation index. This demonstrates the effectiveness of the method in identification of poly (A) sites.
Keywords :
chemistry computing; macromolecules; support vector machines; AdaBoost algorithm; adaptive boosting; arabidopsis messenger RNA polyadenylation sites; support vector machine; Bioinformatics; Boosting; Gene expression; Humans; Information science; Machine learning; Machine learning algorithms; RNA; Sequences; Space technology;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.224
