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Table 1 Comparison with existing methods

From: Identification of microRNA precursors based on random forest with network-level representation method of stem-loop structure

Methods Complete dataset Training dataset Testing dataset Results for testing dataset Results for Independent dataset
  Pos Neg Pos Neg Pos Neg SE SP Plant (Acc) Virus (Acc) Total (Acc)
Triplet-SVM 193 1168 163 168 30 1000 0.933 0.881 0.882 0.843 0.877a
microPred 691 9248 SMOTE Outer-5-fold-CV 0.900 0.973 0.841 0.939 0.853b
Our method 3928 8897 3000 3000 928 5897 0.873 0.911 0.976 0.913 0.970
  1. Triplet-SVM is a SVM-based method with triplet elements that represent information of pre-miRNA stem-loop structure. There is an extension called MiPred.
  2. microPred combined the new RNAfold-related, Mfold-related, and pair-related features with 29 'global and intrinsic' features introduced in the miPred approach.
  3. a 178 virus and 1232 plant sequences were used, as samples with multiple loops were filtered out by Triplet-SVM.
  4. b 196 virus and 1389 (the length less than 300) plant sequences were submitted to microPred web server.
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BMC Bioinformatics

ISSN: 1471-2105

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