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Ligand-based virtual screening using binary kernel discrimination

By B. Chen, R.F. Harrison, J. Hert, C. Mpanhanga, P. Willett and D.J. Wilton

Abstract

This paper discusses the use of a machine-learning technique called binary kernel discrimination (BKD) for virtual screening in drug- and pesticide-discovery programmes. BKD is compared with several other ligand-based tools for virtual screening in databases of 2D structures represented by fragment bit-strings, and is shown to provide an effective, and reasonably efficient, way of prioritising compounds for biological screening

Publisher: Taylor & Francis
Year: 2005
OAI identifier: oai:eprints.whiterose.ac.uk:7691

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