Identifying translation initiation sites in prokaryotes using support vector machine | |
Gao, Tingting1; Yang, Zhixia2,3; Wang, Yong3![]() | |
刊名 | JOURNAL OF THEORETICAL BIOLOGY
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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. |
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