Predicting protein targets for drug-like compounds using transcriptomics.

PLoS Comput Biol · 2018 · PMC6300300 · PMID 30532261

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extremely significantno p-value reported

Our RF produced an AUC of 0.77 while, in sharp contrast, random rankings (based on 20000 permutations) leads to only 7% of drugs with targets in the 100, indicating that both our training/testing and LOOCV results are extremely significant ( S1 Fig ).

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