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. 2008 Jul 1;24(13):i366–i374. doi: 10.1093/bioinformatics/btn186

Table 1.

Average AUC values using different prediction models and different training set sizes

Models Training set size
1% 5% 10% 25%
NCI antiviral dataset
MCS-based 57.9 (3.0) 64.0 (2.4) 67.0 (1.3) 70.0 (0.9)
AP-based 58.2 (3.1) 63.7 (1.8) 65.8 (1.8) 68.9 (1.5)
Hybrid 61.3 (3.4) 66.7 (1.9) 69.2 (1.3) 71.6 (1.2)
NCI anticancer dataset
MCS-based 60.3 (2.8) 65.4 (1.8) 68.0 (1.7) 70.9 (1.3)
AP-based 59.3 (3.3) 65.2 (1.8) 67.8 (1.7) 70.9 (1.8)
Hybrid 62.7 (3.2) 69.2 (1.8) 71.8 (1.4) 74.8 (1.2)

The MCS-based model uses the absolute MCS sizes to represent a chemical structure as a vector. The AP-based model uses the AP-based similarity, and the hybrid model concatenates the vectors from both previous models. SDs are given in parentheses.

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