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Table 8 Performance comparison with MCODE, COACH, CMC and ClusterONE on four PIN datasets

From: Predicting protein complex in protein interaction network - a supervised learning based method

Dataset

Method

Num

P

R

F

Sn

PPV

Acc

DIP

MCODE

79

0.5570

0.1332

0.2150

0.2758

0.6880

0.4356

 

COACH

747

0.4351

0.5195

0.4735

0.4779

0.6921

0.5751

 

CMC

262

0.5687

0.4102

0.4766

0.4791

0.7241

0.5890

 

ClusterONE

354

0.5113

0.4072

0.4533

0.3903

0.7124

0.5273

 

Ours

613

0.6232

0.5269

0.5710

0.4764

0.7375

0.5927

Gavin

MCODE

78

0.8718

0.2809

0.4249

0.4174

0.7017

0.5412

 

COACH

326

0.7393

0.6086

0.6676

0.6277

0.7162

0.6705

 

CMC

202

0.7228

0.4176

0.5294

0.3817

0.7067

0.5194

 

ClusterONE

200

0.8050

0.5693

0.6669

0.6211

0.7048

0.6617

 

Ours

275

0.8145

0.5730

0.6728

0.5083

0.7526

0.6185

Krogan

MCODE

63

0.6349

0.1544

0.2484

0.4439

0.4865

0.4642

 

COACH

570

0.4439

0.4865

0.4642

0.502

0.6575

0.5745

 

CMC

242

0.5909

0.3555

0.4439

0.3263

0.7215

0.4852

 

ClusterONE

258

0.5349

0.4381

0.4817

0.4865

0.7567

0.6067

 

Ours

465

0.5591

0.4955

0.5254

0.4944

0.7189

0.5962

Collins

MCODE

111

0.8468

0.431

0.5713

0.5438

0.7600

0.6429

 

COACH

251

0.6972

0.5651

0.6243

0.6275

0.7931

0.7054

 

CMC

172

0.6919

0.4234

0.5253

0.4882

0.7336

0.5985

 

ClusterONE

180

0.8222

0.5958

0.6909

0.6526

0.7275

0.6891

 

Ours

150

0.8133

0.5096

0.6266

0.6338

0.7431

0.6863