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Table 1 Performance of the Univariate Bayesian annotation approach. Re-annotation of the filtered ENZYME database with the univariate Bayesian approach. Since we systematically sample 10 enzymes to calculate the probabilities for a protein to belong to each functional class (See Different strategies of annotation), probabilities can only take one of the following eleven values: 0, 0.1, ..., 0.9, 1. We report for each assignment probability level and globally the number of correct annotations, the number of annotation errors and the corresponding error rate and coverage of the database.

From: Probabilistic annotation of protein sequences based on functional classifications

Univariate Bayesian approach

Assignment probability

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

TOT

Correct annotations

84

109

103

99

119

177

252

302

437

726

25387

27795

Annotation errors

27

15

5

11

13

23

41

29

31

45

53

293

Error rate (%)

24.3

12.1

4.6

10.0

9.8

11.5

14.0

8.8

6.6

5.8

0.21

1.04

Coverage (%)

0.4

0.4

0.4

0.4

0.5

0.7

1.0

1.2

1.7

2.7

90.6

100.0