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Table 12 Comparisons between the different methods on the Bootstrap0.094 network

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

   Method
   MCL MCLO MCL-CAw CMC HACO
  #Predicted 203 204 199 203 127
Wodak
(#172)
#Matched 76 76 79 110 80
  Precision 0.374 0.372 0.397 0.542 0.630
  #Derived 85 85 88 106 90
  Recall 0.494 0.494 0.512 0.616 0.523
MIPS
(#168)
#Matched 44 45 47 67 49
  Precision 0.271 0.220 0.236 0.330 0.386
  #Derived 56 57 59 69 63
  Recall 0.333 0.339 0.351 0.411 0.375
Aloy
(#76)
#Matched 56 55 57 76 59
  Precision 0.276 0.269 0.286 0.374 0.465
  #Derived 55 55 58 63 60
  Recall 0.724 0.723 0.763 0.829 0.789
  1. Methods considered: MCL, MCLO, MCL-CAw, CMC and HACO. HACO performed the best in terms of precision, while CMC performed the best in terms of recall. MCL-CAw was positioned third in both precision and recall. #Matched: #Predictions matching some benchmark complex(es). #Derived: #Benchmark complexes derived by some predicted complex(es).
  2. The Bootstrap 0.094 network
  3. #Proteins 2719; #Interactions 10290