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Table 1 Prediction accuracy using various features and some combinations, with the AUC scores of different models shown in the table (TAD–Lactuca_RF represent Random Forests Model and TAD–Lactuca_MLP represents Multi-Layer Perceptron, the details of them are introduced at section 3.2.3.)

From: A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information

Methods

Features

ALL

CTCF+Histones

CTCF

Histones

3-Mer

HubPredictor

–

0. 774

0.703

–

–

TAD–Lactuca_RF

0.867

0. 817

0. 754

0. 773

0.636

TAD–Lactuca_MLP

0.812

0. 810

0. 752

0. 756

0.592