BMC Bioinformatics

Table 8 Comparisons between the different methods on the unscored Gavin+Krogan network

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

		*Method*
		MCL	MCL-CA	MCL-CAw	COACH	CORE	CMC	HACO
	#Predicted	242	219	310	447	386	113	278
Wodak (#182)	#Matched	55	49	77	62	83	60	78
	Precision	0.226	0.224	0.248	0.139	0.215	0.531	0.281
	#Derived	62	49	77	49	83	60	85
	Recall	0.338	0.269	0.423	0.269	0.456	0.330	0.467
MIPS (#177)	#Matched	35	42	53	45	59	41	45
	Precision	0.143	0.192	0.171	0.101	0.153	0.363	0.162
	#Derived	40	42	53	38	59	41	57
	Recall	0.226	0.237	0.300	0.215	0.333	0.232	0.322
Aloy (#76)	#Matched	43	41	52	54	59	43	59
	Precision	0.179	0.187	0.168	0.121	0.153	0.381	0.212
	#Derived	42	41	52	37	59	43	59
	Recall	0.556	0.539	0.684	0.487	0.776	0.566	0.776

Methods considered: MCL, MCL-CA, MCL-CAw, COACH, CORE, CMC and HACO. CMC performed the best in terms of precision, while HACO and CORE performed the best in terms of recall. MCL-CAw stood third among of the seven algorithms in both precision and recall. #Matched: #Predictions matching some benchmark complex(es). #Derived: #Benchmark complexes derived by some predicted complex(es).
The unscored Gavin+Krogan network
#Proteins 2964; #Interactions 13507

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ISSN: 1471-2105

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