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Table 2 AUROC and AUPR indexes for curated and PIDC networks with conventional GRN inference and ModularBoost

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

Methods Curated GSD-1 Curated GSD-50 Curated GSD-70
AUROC AUPR AUROC AUPR AUROC AUPR
Ridge 0.545 0.234 0.517 0.232 0.530 0.234
Linear regression 0.520 0.225 0.507 0.220 0.467 0.204
TIGRESS 0.547 0.233 0.548 0.253 0.523 0.249
GRNBoost2 0.547 0.230 0.566 0.258 0.550 0.258
ModularBoost 0.549 0.234 0.559 0.260 0.553 0.259
Methods PIDC E. coli-S PIDC E. coli-LL PIDC E. coli-LH
AUROC AUPR AUROC AUPR AUROC AUPR
Ridge 0.667 0.065 0.594 0.024 0.540 0.015
Linear regression 0.461 0.010 0.518 0.012 0.479 0.011
TIGRESS 0.676 0.068 0.612 0.035 0.601 0.020
GRNBoost2 0.659 0.056 0.558 0.038 0.570 0.034
ModularBoost 0.678 0.074 0.624 0.039 0.618 0.028
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