Skip to main content

Advertisement

Table 2 Numbers of samples in each of the eleven newly-designed datasets

From: Significant improvement of miRNA target prediction accuracy in large datasets using meta-strategy based on comprehensive voting and artificial neural networks

Dataset Associated individual predictors No. of original samples No. of non-redundant samples No. of positive samples No. of negative samples No. of miRNAs No. of mRNAs
D4 miRanda, MiRDB, PITA, TargetScan 45,517 22,446 1844 20,602 211 6747
D3–1 miRanda, MiRDB, PITA 29,486 9271 1339 7932 212 4619
D3–2 miRanda, MiRDB, TargetScan 7584 2478 198 2280 201 1097
D3–3 miRanda, PITA, TargetScan 107,813 5529 1220 4309 205 3541
D3–4 MiRDB, PITA, TargetScan 66,384 2984 864 2120 323 1946
D2–1 miRanda, MiRDB 5269 892 199 693 186 641
D2–2 miRanda, PITA 216,923 974 457 517 202 883
D2–3 miRanda, TargetScan 32,566 429 151 278 162 342
D2–4 MiRDB, PITA 29,531 810 455 355 165 645
D2–5 MiRDB, TargetScan 256,784 430 174 256 259 337
D2–6 PITA, TargetScan 384,944 363 179 184 175 288