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Table 3 Frequency that a gene is predicted by a miR by number of algorithms

From: Differential expression of microRNAs as predictors of glioblastoma phenotypes

  Number of   Number of
  Algorithms   Algorithms
Gene 3 2 1 Gene 3 2 1
CCND1 16 4 4 IGF1R 0 22 3
E2F3 12 11 1 SOS1 0 16 10
AKT3 11 9 6 PIK3R1 0 16 2
PDGFRA 11 4 1 IGF1 0 15 14
PDGFB 11 0 1 E2F2 0 11 8
RB1 10 2 3 PTEN 0 10 14
KRAS 9 3 0 PTENP1 0 10 14
PDGFRB 7 3 0 MAPK1 0 8 5
CDK6 6 8 5 TP53 0 8 2
CALM1 6 1 12 PIK3CD 0 5 2
CDKN1A 5 8 3 TGFA 0 3 1
PIK3R3 5 6 6 SHC4 0 3 0
CALM2 5 4 3 PDGFA 0 2 4
CAMK2D 5 4 2 PIK3CA 0 1 3
RAF1 5 3 0 SHC2 0 1 0
CALM3 5 2 2 AKT2 0 0 9
CAMK2G 5 1 5 CAMK2B 0 0 4
E2F1 4 1 0 PRKCB1 0 0 4
CSDE1 3 4 14 MAPK3 0 0 3
MAP2K1 3 4 1 EGF 0 0 2
PLCG1 3 3 1 EGFR 0 0 2
PIK3R2 3 2 3 PRKCG 0 0 2
FRAP1 3 0 1 BRAF 0 0 1
GRB2 2 0 1 CDK4 0 0 1
PRKCA 1 1 3 CDKN2A 0 0 1
SHC1 1 0 1 MAPK 0 0 1
     SOS2 0 0 1
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