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Table 3 Performance comparison CDUN with other approaches using CYC2008 as benchmark

From: An uncertain model-based approach for identifying dynamic protein complexes in uncertain protein-protein interaction networks

PPI Dataset

Methods

Precision

Recall

F-score

Sn

PPV

Accuracy

DIP

CDUN

0.6

0.551

0.575

0.431

0.641

0.526

CSO

0.497

0.623

0.553

0.538

0.631

0.582

Cluster ONE

0.337

0.441

0.382

0.378

0.696

0.513

COAN

0.41

0.597

0.486

0.445

0.529

0.483

COACH

0.307

0.602

0.406

0.544

0.456

0.498

CMC

0.485

0.428

0.455

0.306

0.643

0.443

HUNTER

0.852

0.119

0.208

0.164

0.644

0.325

MCODE

0.423

0.14

0.21

0.282

0.362

0.32

TransClust

0.13

0.674

0.218

0.622

0.725

0.672

SpecClust

0.122

0.331

0.179

0.548

0.529

0.538

MIPS

CDUN

0.438

0.331

0.377

0.244

0.612

0.387

CSO

0.391

0.344

0.365

0.283

0.641

0.426

Cluster ONE

0.273

0.267

0.27

0.235

0.725

0.412

COAN

0.356

0.352

0.354

0.261

0.636

0.407

COACH

0.239

0.347

0.283

0.317

0.385

0.35

CMC

0.335

0.322

0.328

0.361

0.468

0.411

HUNTER

0.538

0.14

0.222

0.289

0.333

0.31

MCODE

0.365

0.153

0.215

0.189

0.572

0.329

TransClust

0.145

0.623

0.236

0.544

0.71

0.621

SpecClust

0.095

0.182

0.125

0.41

0.37

0.389

STRING

CDUN

0.446

0.674

0.537

0.715

0.518

0.609

Cluster ONE

0.13

0.343

0.188

0.671

0.494

0.569

COACH

0.181

0.458

0.26

0.963

0.154

0.385

HUNTER

0.5

0.017

0.033

0.107

0.353

0.194

MCODE

0.079

0.131

0.099

0.681

0.257

0.418

TransClust

0.11

0.517

0.181

0.842

0.528

0.667

SpecClust

0.066

0.347

0.111

0.652

0.519

0.582

  1. The highest value of each dataset is in bold. Core_thresh is set 0.4 for CDUN