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Abstract: Automated high-throughput drug screening constitutes a critical emerging approach in modern pharmaceutical research. The statistical task of interest is that of discriminating active versus inactive molecules given a target molecule, in order to rank potential drug candidates for further testing. Because the core problem is one of ranking, our approach concentrates on accurate estimation of unknown class probabilities, in contrast to popular non-probabilistic methods which simply estimate... (Update)
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BibTeX entry: (Update)
@misc{ gray-highdimensional,
author = "Alexander Gray and Paul Komarek and Ting Liu and Andrew Moore",
title = "High-Dimensional Probabilistic Classification For Drug Discovery",
url = "citeseer.ist.psu.edu/gray04highdimensional.html" }
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