This article is part of the supplement: Proceedings of the 21st International Conference on Genome Informatics (GIW2010)
Research
MiRenSVM: towards better prediction of microRNA precursors using an ensemble SVM classifier with multi-loop features
1 Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai 200433, China
2 Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
BMC Bioinformatics 2010, 11(Suppl 11):S11 doi:10.1186/1471-2105-11-S11-S11
Published: 14 December 2010Additional files
Additional file 1:
Description: We surveyed pre-miRNA registered in miRBase with secondary multi-loop brunch secondary structure or with a MFE higher than -16 kal/mol, and showed the results in Table S1 and S2. Table S3 lists the 27 bran-new hsa and aga pre-miRNA sequences used as testing set. Table S4 shows the detail results of 27 other animal genomes. We also supplied some detail of the features used in the main paper
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Additional file 2:
Description: An Anopheles gambiae (aga) ncRNA dataset is built by selecting sequences whose secondary structures can be predicted by RNAfold and UNAfold in Rfam9.1. Furthermore, sequences with identity higher than 90% are removed.
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