Table 4 Performance of each prediction algorithm on six single organism T1 PGDBs. \(\downarrow\) indicates that a lower score is better while for \(\uparrow\) a higher score is better. The best performing method is bold for each metric. PGDB names have been shortened for readability

0.0685

0.0744

0.1124

0.0507

0.0416

0.0669

0.0372

0.0424

0.0649

0.0257

0.0234

0.0530

0.0804

0.0633

0.1069

0.0550

0.0380

0.0590

0.0435

0.0954

0.1560

0.0649

0.0443

0.0776

0.0146

0.0190

0.0412

0.0146

0.0063

0.0119

0.0162

0.0226

0.0447

0.0178

0.0075

0.0131

0.0190

0.0190

0.0483

0.0174

0.0075

0.0127

0.0158

0.0170

0.0360

0.0154

0.0079

0.0099

0.6626

0.6091

0.6799

0.6517

0.4511

0.5099

0.8105

0.7688

0.8502

0.8106

0.6667

0.6589

0.6187

0.6686

0.7372

0.6480

0.4731

0.5455

0.8662

0.6080

0.7377

0.7273

0.4161

0.4561

0.9963

0.9873

0.9833

1.0000

0.9863

0.9739

0.9890

0.9744

0.9649

0.9742

0.9474

0.9437

0.9675

0.9793

0.9641

0.9793

0.9359

0.9441

0.9819

0.9797

0.9861

0.9847

0.9241

0.9573

0.8893

0.9104

0.8373

0.9476

0.9540

0.8857

0.9055

0.8817

0.8235

0.9345

0.6437

0.4857

0.8827

0.8459

0.7314

0.8603

0.9080

0.8914

0.7590

0.3835

0.3529

0.3319

0.7126

0.6229

0.8827

0.8387

0.8098

0.8384

0.8276

0.8514

0.8762

0.8172

0.8078

0.8253

0.8276

0.8629

0.8730

0.8459

0.7902

0.8253

0.8391

0.8686

0.8860

0.8638

0.8333

0.8428

0.8391

0.8971

0.7594

0.7299

0.7504

0.7722

0.6125

0.6472

0.8554

0.8214

0.8367

0.8682

0.6550

0.5592

0.7275

0.7468

0.7343

0.7392

0.6220

0.6768

0.8090

0.4703

0.4775

0.4735

0.5254

0.5266

0.9361

0.9070

0.8882

0.9121

0.9000

0.9085

0.9292

0.8889

0.8794

0.8936

0.8834

0.9015

0.9178

0.9077

0.8685

0.8957

0.8848

0.9048

0.9315

0.9181

0.9033

0.9082

0.8795

0.9263