MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences

@inproceedings{Wu2010MiRParaAS,
  title={MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences},
  author={Yonggan Wu and Bo Wei and Haizhou Liu and Tianxian Li and Simon Rayner},
  booktitle={BMC Bioinformatics},
  year={2010}
}
MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets… CONTINUE READING
Highly Influential
This paper has highly influenced 10 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
69 Extracted Citations
48 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 69 extracted citations

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 48 references

Similar Papers

Loading similar papers…