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Table 8 Tool performance to 96 h-LC50 of fish for chemicals within each applicability domains

From: Comparison of seven in silico tools for evaluating of daphnia and fish acute toxicity: case study on Chinese Priority Controlled Chemicals and new chemicals

Chemicals Methods Measures of predictive accuracy ECOSAR T.E.S.T. Danish Q. D. VEGA Read Across Trend Analysis KATE
37 PCCs General Number of inside AD 29 22 19 29 31 30 22
Number of outside AD and missing prediction 8 15 18 8 6 6 15
Qualitative Number of correct 16 9 11 16 11 8 8
Number of incorrect 13 13 8 13 20 23 14
Accuracy inside AD (%) 55 41 58 55 35 26 36
R2AD (toxicity class) 0.66 0.41 0.58 0.57 0.07 0.06 0.35
Quantitative Accuracy within a factor of 10 (%) 83 82 74 90 55 42 86
Accuracy within a factor of 100 (%) 100 95 79 97 81 55 95
Accuracy within a factor of 1000 (%) 100 100 84 100 94 84 100
RMSE (log10 LC50) 0.71 0.87 1.83 0.75 1.47 2.09 0.80
R2AD (log10 LC50) 0.68 0.52 0.57 0.68 0.14 0.00 0.50
86 NCs Qualitative Number of inside AD 58 61 22 50 / / 21
Number of outside AD and missing prediction 28 25 64 36 / / 67
Number of correct 32 25 13 18 / / 7
Number of incorrect 26 36 9 32 / / 12
Accuracy inside AD (%) 55 41 59 36 / / 37
R2AD (toxicity class) 0.37 0.10 0.42 0.03 / / 0.37
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BMC Bioinformatics

ISSN: 1471-2105

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