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Table 2 Performances of DeepEP and comparing models (using gene expression profiles combined with different central indexes (DC, CC, EC, BC, NC, and LAC))

From: DeepEP: a deep learning framework for identifying essential proteins

Model

Accuracy

Precision

Recall

F-measure

AUC

Gene expression + DC

0.803

0.558

0.220

0.315

0.701

Gene expression + CC

0.782

0.446

0.247

0.318

0.667

Gene expression + EC

0.774

0.429

0.293

0.348

0.690

Gene expression + BC

0.789

0.474

0.215

0.296

0.657

Gene expression + NC

0.779

0.432

0.243

0.311

0.670

Gene expression + LAC

0.796

0.533

0.211

0.302

0.672

Gene expression + node2vec

0.826

0.584

0.524

0.552

0.816