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Table 6 Performance of the models built on ChEMBL_22 and ChEMBL_23 data

From: Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery

Method Model data Prediction set Model targets Sensitivity Specificity CCR
QSAR ChEMBL_23 ChEMBL_24 282 0.63 0.80 0.71
MCP_incl ChEMBL_24 282 0.63 0.67 0.65
MCP_excl ChEMBL_24 282 0.56 0.61 0.58
QSAR ChEMBL_22 ChEMBL_23 282 0.64 0.84 0.74
ChEMBL_24 282 0.60 0.81 0.71
MCP_incl ChEMBL_23 282 0.61 0.72 0.66
ChEMBL_24 282 0.61 0.67 0.64
MCP_excl ChEMBL_23 282 0.56 0.68 0.62
ChEMBL_24 282 0.54 0.61 0.57
  1. MCP model results are given at 80% confidence level. MCP_incl and MCP_excl indicate the ‘both’ prediction class was included in the result calculation or was ignored, respectively
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Journal of Cheminformatics

ISSN: 1758-2946

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