Table 1 BC-X corresponds to the BRANE Cut method initialized with the weights of the method X
Network index | 1 | 2 | 3 | 4 | 5 | Average |
|---|---|---|---|---|---|---|
(a) Area Under Precision-Recall for the CLR, ND-CLR, GENIE3, ND-GENIE3 and BRANE Cut methods on the DREAM4 dataset. | ||||||
For each given network, the two maximal improvements are reported in bold | ||||||
CLR | 0.256 | 0.275 | 0.314 | 0.313 | 0.318 | 0.295 |
BC-CLR | 0.282 | 0.308 | 0.343 | 0.344 | 0.356 | 0.327 |
GENIE3 | 0.269 | 0.288 | 0.331 | 0.323 | 0.329 | 0.308 |
BC-GENIE3 | 0.298 | 0.316 | 0.357 | 0.344 | 0.352 | 0.333 |
ND-CLR | 0.254 | 0.250 | 0.324 | 0.318 | 0.331 | 0.295 |
BC-ND-CLR | 0.271 | 0.277 | 0.334 | 0.335 | 0.343 | 0.312 |
ND-GENIE3 | 0.263 | 0.275 | 0.336 | 0.328 | 0.354 | 0.309 |
BC-ND-GENIE3 | 0.275 | 0.312 | 0.367 | 0.346 | 0.368 | 0.334 |
(b) Relative gain obtained using BRANE Cut on different initial weights: CLR, ND-CLR, GENIE3, ND-GENIE3 on the DREAM4 dataset | ||||||
BC-CLR vs CLR | 10.1 % | 11.8 % | 9.1 % | 9.9 % | 11.9 % | 10.6 % |
BC-GENIE3 vs GENIE3 | 10.7 % | 9.9 % | 7.8 % | 6.5 % | 7.0 % | 8.4 % |
BC-ND-CLR vs ND-CLR | 6.6 % | 10.7 % | 3.0 % | 5.5 % | 3.7 % | 5.9 % |
BC-ND-GENIE3 vs ND-GENIE3 | 4.4 % | 13.4 % | 9.2 % | 5.4 % | 3.8 % | 7.2 % |
(c) Post-processing method comparison on the DREAM4 dataset. Relative gain are given for BRANE Cut using CLR (resp. GENIE3) | ||||||
weights compared to ND-CLR (resp. ND-GENIE3) | ||||||
BC-CLR vs ND-CLR | 11 % | 23.2 % | 5.9 % | 8.2 % | 7.5 % | 11.2 % |
BC-GENIE3 vs ND-GENIE3 | 13.8 % | 14.9 % | 6.2 % | 4.9 % | −0.6 % | 7.7 % |