Identifying translation initiation sites in prokaryotes using support vector machine

doi:10.1016/j.jtbi.2009.10.023

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 应用数学研究所

	Identifying translation initiation sites in prokaryotes using support vector machine
	Gao, Tingting 1; Yang, Zhixia 2,3; Wang, Yong3 ; Jing, Ling 1
刊名	JOURNAL OF THEORETICAL BIOLOGY
	2010-02-21
卷号	262 期号:4 页码:644-649
关键词	Translation initiation site prediction Support vector machine Position specific weight matrix
ISSN号	0022-5193
DOI	10.1016/j.jtbi.2009.10.023
英文摘要	Motivation: Gene identification in genomes has been a fundamental and long-standing task in bioinformatics and computational biology. Many computational methods have been developed to predict genes in prokaryote genomes by identifying translation initiation site (TIS) in transcript data. However, the pseudo-TISs at the genome level make these methods suffer from a high number of false positive predictions. In addition, most of the existing tools use an unsupervised learning framework, whose predictive accuracy may depend on the choice of specific organism. Results: In this paper, we present a supervised learning method, support vector machine (SVM), to identify translation initiation site at the genome level. The features are extracted from the sequence data by modeling the sequence segment around predicted TISs as a position specific weight matrix (PSWM). We train the parameters of our SVM through well constructed positive and negative TIS datasets. Then we apply the method to recognize translation initiation sites in E. coli, B. subtilis, and validate our method on two GC-rich bacteria genomes: Pseudomonas aeruginosa and Burkholderia pseudomallei K96243. We show that translation initiation sites can be recognized accurately at the genome level by our method, irrespective of their GC content. Furthermore, we compare our method with four existing methods and demonstrate that our method outperform these methods by obtaining better performance in all the four organisms. (C) 2009 Published by Elsevier Ltd.
资助项目	National Natural Science Foundation of China[10631070] ; National Natural Science Foundation of China[10801112] ; National Natural Science Foundation of China[10801131] ; Ph.D. Graduate Start Research Foundation[BS080101]
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology
语种	英语
出版者	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
WOS记录号	WOS:000274676700008
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/9615]
专题	应用数学研究所
通讯作者	Jing, Ling
作者单位	1.China Agr Univ, Coll Sci, Beijing 100083, Peoples R China 2.Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Gao, Tingting,Yang, Zhixia,Wang, Yong,et al. Identifying translation initiation sites in prokaryotes using support vector machine[J]. JOURNAL OF THEORETICAL BIOLOGY,2010,262(4):644-649.
APA	Gao, Tingting,Yang, Zhixia,Wang, Yong,&Jing, Ling.(2010).Identifying translation initiation sites in prokaryotes using support vector machine.JOURNAL OF THEORETICAL BIOLOGY,262(4),644-649.
MLA	Gao, Tingting,et al."Identifying translation initiation sites in prokaryotes using support vector machine".JOURNAL OF THEORETICAL BIOLOGY 262.4(2010):644-649.