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Table 6 Module identification evaluation of the DREAM5 networks

From: ModularBoost: an efficient network inference algorithm based on module decomposition

Methods Module gold DREAM5 E. coli DREAM5 Yeast
Sisima Macisaac
ICA-FDR Minimal 0.206 0.102 0.107
Strict 0.193 0.090 0.073
Interconnected 0.199 0.102 0.094
ICA-FDR2 Minimal 0.203 0.093 0.099
Strict 0.190 0.082 0.069
Interconnected 0.189 0.094 0.087
ICA-zscore Minimal 0.192 0.086 0.096
Strict 0.202 0.070 0.064
Interconnected 0.183 0.081 0.086
PCA decomposition Minimal 0.101 0.047 0.047
Strict 0.100 0.046 0.042
Interconnected 0.097 0.047 0.048
K-means Minimal 0.173 0.070 0.076
Strict 0.178 0.059 0.055
Interconnected 0.146 0.063 0.066
  1. \(F_{rr}\) indexes were calculated by comparing the predicted and known modules. High \(F_{rr}\) values demonstrate high consistency between the predictions and module gold standards. Three types of gene modules, i.e. Minimal, Strict and Interconnected were taken into consideration. Highest values in each type of gene modules for networks were displayed in bold