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Table 1 The results of predicting real-value distance map and multi-class distance map at the same time versus predicting real-value distance separately on 43 CASP13 hard domains

From: DeepDist: real-value inter-residue distance prediction with deep residual convolutional network

 

L/5 (Precision)

L/2 (Precision)

L (Precision)

MSE

Pearson coefficient

Experiment 1

0.699

0.580

0.446

1.151

0.979

Experiment 2

0.687

0.558

0.430

1.282

0.978

  1. MSE: average mean square error between predicted distances and true distances; Pearson coefficient: the Pearson’s correlation between predicted distance and true distance
  2. Experiment 1: real-value distance prediction by training real-value distance prediction and multi-class distance prediction simultaneously
  3. Experiment 2: real-value distance prediction by training real-value distance prediction alone. The two experiments used the same input features PLM and the same model architecture PLM_Net
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BMC Bioinformatics

ISSN: 1471-2105

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