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Effectively selecting therapeutic targets from the sizeable lists that are emerging from large-scale multi-omics initiatives is a key challenge in drug discovery. This article describes an objective, systematic computational assessment of biological and chemical space that can be applied to any human gene set to prioritize targets for further evaluation, and demonstrates its use on a set of 479 cancer-associated genes to identify new opportunities for drug discovery and repurposing.
