Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40947
Title: Identification of microrna precursors via SVM
Authors: Yang, L.H. 
Hsu, W. 
Lee, M.L. 
Wong, L. 
Issue Date: 2006
Source: Yang, L.H.,Hsu, W.,Lee, M.L.,Wong, L. (2006). Identification of microrna precursors via SVM. Series on Advances in Bioinformatics and Computational Biology 3 : 267-276. ScholarBank@NUS Repository.
Abstract: 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.
Source Title: Series on Advances in Bioinformatics and Computational Biology
URI: http://scholarbank.nus.edu.sg/handle/10635/40947
ISBN: 1860946232
ISSN: 17516404
Appears in Collections:Staff Publications

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