Figure 5.

Chemical predictions for Prostate, Lung, and Breast Cancer datasets clustered by PubChem BioActivity. Highly significant chemical prediction p-values for the prostate, lung, and breast cancer datasets (p = 0.001, 0.001, 0.01, for the prostate, lung, and breast cancer datasets) are reordered by their BioActivity similarity computed by PubChem. A column represents the cancer analyzed and each cell corresponds to the chemical-gene set association -log10(p-value). Examples of correlation between BioActivity similarity and chemical-gene set significance include the sodium arsenite, sodium arsenate, and Doxorubicin cluster (labeled in orange), the Genistein, Estradiol, Ethinyl Estradiol, and Diethylbisterol and Progesterone, Tretinoin, and Corticosterone clusters (labeled in purple). Other examples of BioActivity similarity and chemical-gene set association include chemicals vinclozolin, tert-Butylhydroperoxide, and Carbon Tetrachloride (outlined in blue).

Patel and Butte BMC Medical Genomics 2010 3:17   doi:10.1186/1755-8794-3-17
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