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Table 4 MCL-CAw performed considerably better than MCL in the presence of natural noise

From: MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

PPI Network #Proteins #Interactions Avg node deg #Derived MCL complexes (Recall) MCL-CAw
Consol3.19 1622 9704 11.96 79 (0.545) 82 (0.566)
Consol0.623 5423 102393 37.76 74 (0.321) 84 (0.375)
ICD(Cons3.19) 1161 8688 14.96 58 (0.408) 63 (0.443)
ICD(Cons0.623) 1273 19996 31.41 52 (0.353) 56 (0.381)
FSW(Cons3.19) 1123 8694 15.48 59 (0.401) 65 (0.442)
FSW(Cons0.623) 1341 20696 30.87 54 (0.360) 57 (0.380)
  1. The Consolidated3.19 and Consolidated0.623 networks were subsets of the Consolidated network [11] derived with PE cut-offs 3.19 and 0.623, respectively. We ran ICD and FSW schemes on these networks. Consolidated0.623 had significant amount of false positives (about 81%) that were discarded by the scoring. The performance of MCL-CAw was only marginally better than MCL on Consolidated3.19, but MCL-CAw performed considerably better than MCL on the "more noisy" Consolidated0.623.