Prediction of mRNA polyadenylation sites by support vector machine

被引:92
作者
Cheng, Yiming
Miura, Robert M.
Tian, Bin [1 ]
机构
[1] Univ Med & Dent New Jersey, New Jersey Med Sch, Dept Biochem & Mol Biol, Newark, NJ 07101 USA
[2] New Jersey Inst Technol, Dept Math Sci, Newark, NJ 07102 USA
关键词
D O I
10.1093/bioinformatics/btl394
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
mRNA polyadenylation is responsible for the 3' end formation of most mRNAs in eukaryotic cells and is linked to termination of transcription. Prediction of mRNA polyadenylation sites [poly(A) sites] can help identify genes, define gene boundaries, and elucidate regulatory mechanisms. Current methods for poly(A) site prediction achieve moderate sensitivity and specificity. Here, we present a method using support vector machine for poly(A) site prediction. Using 15 cis-regulatory elements that are over-represented in various regions surrounding poly(A) sites, this method achieves higher sensitivity and similar specificity when compared with polyadq, a common tool for poly(A) site prediction. In addition, we found that while the polyadenylation signal AAUAAA and U-rich elements are primary determinants for poly(A) site prediction, other elements contribute to both sensitivity and specificity of the prediction, indicating a combinatorial mechanism involving multiple elements when choosing poly(A) sites in human cells.
引用
收藏
页码:2320 / 2325
页数:6
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