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These highlighted datasets provide 22, 46, and 61 characters, respectively, to the present analysis, a total of 72.8%.
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We conduct some experiments for evaluating the efficiency, and demonstrate: (1) the utilization of information within incomplete instances is of benefit to easily capture the distribution of a dataset; and (2) the NIIA method outperforms the existing methods in accuracy, and this advantage is clearly highlighted when datasets have a high missing ratio.
Figure 15 Endpoint values highlighted (Caco2 dataset).
Figure 13 LogD values highlighted (Caco2 dataset).
Figure 16 Endpoint values highlighted (PBDE dataset).
The cell viability datasets highlighted above provide an example of the meta-analysis possible with data from a curated database.
The compounds of the Caco2 dataset, highlighted according to their endpoint value.
The compounds of the Caco2 dataset, highlighted according to their LogD feature value.
The compounds of the PBDE dataset, highlighted according to their endpoint value.
The compounds of the PBDE dataset, highlighted according to the structural fragment "Br-c c c-O".
q-value < 0.01 is considered as significant, and q-values for pathways with significant q-values for at least two datasets are highlighted in bold.
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