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Table 2 Scoring model performance

From: In silico miRNA prediction in metazoan genomes: balancing between sensitivity and specificity

Scoring model description # a Wt b LDF c Chi – Square d AUCe AUC e AUC e Selectivity f
      Nematoda H. sapiens Metazoa 95% 75%
Default models g
Metazoa 3,902 - 0.95 9.95e-7 0.9760 0.9764 0.9814 12.57 74.06
H. sapiens 781 - 0.95 0.090 0.9733 0.9794 0.9806 11.04 68.90
C. elegans 131 - 0.95 0.405 0.9747 0.9638 0.9735 7.73 41.43
Optimized models g
Metazoa 3902 Y 0.90 9.95e-7 0.9813 0.9848 0.9874 21.92 105.7
H. sapiens 781 Y 0.90 0.090 0.9798 0.9870 0.9871 21.93 87.36
C. elegans 131 Y 0.90 0.405 0.9817 0.9775 0.9835 16.65 75.34
  1. a Number of miRNAs in taxonomic set
  2. b -; No weighting (weight = 1), Y; weighting individual descriptors by the square root of their discriminative power (Table 1)
  3. c LDF parameterized at 95% or 90% of the CDF
  4. d Goodness-of-fit is evaluated by averaging Chi-square test statistics of all 40 descriptors
  5. e A rea u nder the c urve of ROC curves measured on the taxonomic sets of known miRNA hairpins from Nematodes (211 miRNA hairpins), H. sapiens (781) and Metazoa (3,902) versus 200,000 randomly selected genomic hairpins from C. elegans.
  6. f Selectivity expressed at 95% and 75% sensitivity, with sensitivity measured on the taxonomic set of Metazoa, specificity measured on set of 3,526,115 C. elegans genomic hairpins.
  7. g Scorings models composed of the subset of 18 most informative descriptors