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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
  1. 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).
  2. The unscored Gavin+Krogan network
  3. #Proteins 2964; #Interactions 13507
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BMC Bioinformatics

ISSN: 1471-2105

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