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2012
L. L. Hu, Huang, Y., Wang, Q. C., Zou, Q., and Jiang, Y., Benchmark comparison of ab initio microRNA identification methods and software, vol. 11, pp. 4525-4538, 2012.
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Computational identification and characteristics of novel microRNAs from the silkworm (Bombyx mori L.). Mol. Biol. Rep. 37: 3171-3176. http://dx.doi.org/10.1007/s11033-009-9897-4 PMid:19823945   Huang Y, Shen XJ, Zou Q, Wang SP, et al. (2011a). Biological functions of microRNAs: a review. J. Physiol. Biochem. 67: 129-139. http://dx.doi.org/10.1007/s13105-010-0050-6 PMid:20981514   Huang Y, Zou Q, Wang SP, Tang SM, et al. (2011b). The discovery approaches and detection methods of microRNAs. Mol. Biol. Rep. 38: 4125-4135. http://dx.doi.org/10.1007/s11033-010-0532-1 PMid:21107708   Jiang P, Wu H, Wang W, Ma W, et al. (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res. 35: W339-W344. http://dx.doi.org/10.1093/nar/gkm368 PMid:17553836 PMCid:1933124   Kumar S, Ansari FA and Scaria V (2009). 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Large-scale sequencing reveals 21U-RNAs and additional microRNAs and endogenous siRNAs in C. elegans. Cell 127: 1193-1207. http://dx.doi.org/10.1016/j.cell.2006.10.040 PMid:17174894   Sankoff D, Kruskal JB, Mainville S and Cedergren RJ (1983). Fast Algorithms to Determine RNA Secondary Structures Containing Multiple Loops. In: Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison (Sankoff D and Kruskal JB, eds.). Chapter 3. Addison-Wesley, Reading, 93-120.   Sewer A, Paul N, Landgraf P, Aravin A, et al. (2005). Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 6: 267. http://dx.doi.org/10.1186/1471-2105-6-267 PMid:16274478 PMCid:1315341   Wang X, Zhang J, Li F, Gu J, et al. (2005). MicroRNA identification based on sequence and structure alignment. Bioinformatics 21: 3610-3614. http://dx.doi.org/10.1093/bioinformatics/bti562 PMid:15994192   Wu Y, Wei B, Liu H, Li T, et al. (2011). MiRPara: a SVM-based software tool for prediction of most probable microRNA   Genetics and Molecular Research 11 (4): 4525-4538 (2012) ©FUNPEC-RP www.funpecrp.com.br   L.L. Hu et al. 4538 coding regions in genome scale sequences. BMC Bioinformatics 12: 107.   Xue C, Li F, He T, Liu GP, et al. (2005). Classification of real and pseudo microRNA precursors using local structuresequence features and support vector machine. BMC Bioinformatics 6: 310. http://dx.doi.org/10.1186/1471-2105-6-310 PMid:16381612 PMCid:1360673   Yousef M, Nebozhyn M, Shatkay H, Kanterakis S, et al. (2006). Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier. Bioinformatics 22: 1325-1334. http://dx.doi.org/10.1093/bioinformatics/btl094 PMid:16543277   Zeng Y, Yi R and Cullen BR (2005). Recognition and cleavage of primary microRNA precursors by the nuclear processing enzyme Drosha. 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