Identification of microrna precursors via SVM

Series on Advances in Bioinformatics and Computational Biology3267-27

October 9, 2005 15:2 Proceedings Trim Size: 9.75in x 6.5in ”SVM-based Identification of microRNA precursors” IDENTIFICATION OF MICRORNA PRECURSORS VIA SVM

MiRNAs are short non-coding RNAs that regulate gene expression. While the first miRNAs were discovered using experimental methods, experimental miRNA identification remains technically challenging and incomplete. This calls for the development of computational approaches to complement experimental approaches to miRNA gene identification. We propose in this paper a de novo miRNA precursor prediction method. This method follows the “feature generation, feature selection, and feature integration ” paradigm of constructing recognition models for genomics sequences. We generate and identified features based on information in both primary sequence and secondary structure, and use these features to construct SVM-based models for the recognition of miRNA precursors. Experimental results show that our method is effective, and can achieve good sensitivity and specificity. 1