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A semi-supervised learning framework combines (ii) and (iii) and can make predictions which take into account the similarity of the testing compounds to those in the training data and adjust for the reporting selection bias. We illustrate the three methods using publicly available structure-activity data for a large set of compounds reported by GlaxoSmithKline (the Tres Cantos AntiMalarial Set, TCAMS) to inhibit asexual in vitro P. falciparum growth. https//github.com/owatson/PenalizedPrediction. Supplementary data are available at Bioi
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