Maximum-Score Diversity Selection for Early Drug Discovery

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MEINL, Thorsten, Claude OSTERMANN, Michael BERTHOLD, 2011. Maximum-Score Diversity Selection for Early Drug Discovery. In: Journal of Chemical Information and Modeling. 51(2), pp. 237-247. ISSN 1549-9596. eISSN 1549-960X. Available under: doi: 10.1021/ci100426r

@article{Meinl2011-02-28Maxim-12389, title={Maximum-Score Diversity Selection for Early Drug Discovery}, year={2011}, doi={10.1021/ci100426r}, number={2}, volume={51}, issn={1549-9596}, journal={Journal of Chemical Information and Modeling}, pages={237--247}, author={Meinl, Thorsten and Ostermann, Claude and Berthold, Michael} }

Journal of Chemical Information and Modeling, 51 (2011), 2, S. 237-247 Ostermann, Claude Berthold, Michael Ostermann, Claude 2011-07-01T09:56:36Z Meinl, Thorsten terms-of-use 2012-02-27T23:25:04Z Berthold, Michael 2011-02-28 Diversity selection is a common task in early drug discovery. One drawback of current approaches is that usually only the structural diversity is taken into account and activity information is ignored. In this article we present a modified version of diversity selection - which we term "Maximum-Score Diversity Selection" - that additionally takes the estimated or predicted activities of the molecules into account. We show that finding an optimal solution to this problem is computationally very expensive (it is NP-hard) and therefore heuristic approaches are needed.<br />After a discussion of existing approaches we present our new method which is computationally far more efficient but at the same time produces comparable results. We conclude by validating these theoretical differences on several datasets. Maximum-Score Diversity Selection for Early Drug Discovery eng Meinl, Thorsten

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