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

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

PPI Network	#Proteins	#Interactions	Avg node deg	#Derived MCL	complexes (Recall) MCL-CAw
Consol_3.19	1622	9704	11.96	79 (0.545)	82 (0.566)
Consol_0.623	5423	102393	37.76	74 (0.321)	84 (0.375)
ICD(Cons_3.19)	1161	8688	14.96	58 (0.408)	63 (0.443)
ICD(Cons_0.623)	1273	19996	31.41	52 (0.353)	56 (0.381)
FSW(Cons_3.19)	1123	8694	15.48	59 (0.401)	65 (0.442)
FSW(Cons_0.623)	1341	20696	30.87	54 (0.360)	57 (0.380)

The Consolidated_3.19 and Consolidated_0.623 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. Consolidated_0.623 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 Consolidated_3.19, but MCL-CAw performed considerably better than MCL on the "more noisy" Consolidated_0.623.

ISSN: 1471-2105