Prediction of mRNA polyadenylation sites by support vector machine

نویسندگان

  • Yiming Cheng
  • Robert M. Miura
  • Bin Tian
چکیده

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.

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عنوان ژورنال:
  • Bioinformatics

دوره 22 19  شماره 

صفحات  -

تاریخ انتشار 2006