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Table 1 Results of an enhancer identification trial (trial 5 in Table 2) on the independent test dataset

From: iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks

Training : Validation (Ratio 4:1)

ACC (%)

AUC (%)

SN (%)

SP (%)

MCC

Model 1 (Parts 2, 3, 4, 5 : Part 1)

0.756

0.815

0.750

0.765

0.515

Model 2 (Parts 1, 3, 4, 5 : Part 2)

0.753

0.829

0.775

0.730

0.506

Model 3 (Parts 1, 2, 4, 5 : Part 3)

0.740

0.825

0.810

0.670

0.485

Model 4 (Parts 1, 2, 3, 5 : Part 4)

0.776

0.831

0.790

0.765

0.555

Model 5 (Parts 1, 2, 3, 4 : Part 5)

0.746

0.821

0.745

0.750

0.495

Ensemble Model

0.765

0.834

0.790

0.740

0.531

  1. The highest value for each metric is in bold