title: Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.
abstract: tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A new predictor, tRNA-Predict, was designed. We obtained real and pseudo-tRNA sequences as training data sets using tRNAScan-SE and constructed three different tRNA feature sets. We then set up an ensemble classifier, LibMutil, to predict tRNAs from the training data. The positive data set of 623 tRNA sequences was obtained from tRNAdb 2009 and the negative data set was the false positive tRNAs predicted by tRNAscan-SE. Our in silico experiments revealed a prediction accuracy rate of 95.1 % for tRNA-Predict using 10-fold cross-validation. tRNA-Predict was developed to distinguish functional tRNAs from pseudo-tRNAs rather than to predict tRNAs from a genome-wide scan. However, tRNA-Predict can work with the output of tRNAscan-SE, which is a genome-wide scanning method, to improve the tRNAscan-SE annotation results. The tRNA-Predict web server is accessible at http://datamining.xmu.edu.cn/∼gjs/tRNA-Predict.
authors.affiliation: School of Information Science and Technology, Xiamen University, Xiamen 361005, China.|School of Computer Science and Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Quan
authors.initials: Q
authors.lastname: Zou
authors.affiliation: School of Information Science and Technology, Xiamen University, Xiamen 361005, China.
authors.forename: Jiasheng
authors.initials: J
authors.lastname: Guo
authors.affiliation: School of Information Science and Technology, Xiamen University, Xiamen 361005, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Ju
authors.affiliation: School of Information Science and Technology, Xiamen University, Xiamen 361005, China.
authors.forename: Meihong
authors.initials: M
authors.lastname: Wu
authors.affiliation: School of Information Science and Technology, Xiamen University, Xiamen 361005, China.
authors.forename: Xiangxiang
authors.initials: X
authors.lastname: Zeng
authors.affiliation: Software School, Xiamen University, Xiamen 361005, China. hongzl@xmu.edu.cn.
authors.forename: Zhiling
authors.initials: Z
authors.lastname: Hong
mesh_terms: D030561:Databases, Nucleic Acid; D058977:Molecular Sequence Annotation / Q000379:methods*; D012343:RNA, Transfer / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D012343:RNA, Transfer
keywords: annotation; ensemble classifier; machine learning; tRNA; tRNAscan-SE