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Table 1 Logistic regression to predict the similarity, or otherwise, of training-set molecule-pairs using different types of fingerprint

From: The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation

Fingerprint

β0

β1

R 2

t LR

AUC

BCI

−12.758

2.128

0.906

0.599

0.990

Daylight

−10.677

1.850

0.884

0.577

0.986

ECFC4

−9.207

2.438

0.878

0.378

0.983

ECFP4

−12.754

2.524

0.894

0.505

0.988

MDL

−9.022

1.380

0.812

0.654

0.973

Unity

−12.347

1.956

0.884

0.631

0.987

  1. The columns contain the β0 and β1 values for the logistic regression model, the Nagelkerke R2 value, the computed value for t LR and the AUC for the ROC curve.
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Journal of Cheminformatics

ISSN: 1758-2946

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