Chen, B., Harrison, R.F., Hert, J. et al. (3 more authors) (2005) Ligand-based virtual screening using binary kernel discrimination. Molecular Simulation, 31 (8). pp. 597-604. ISSN 0892-7022
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2005 Taylor & Francis. This is an author produced version of a paper subsequently published in Molecular Simulation. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Binary kernel discrimination, Circular substructure, Fingerprints, Similarity searching, Virtual screening |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > Department of Chemistry (Sheffield) |
Depositing User: | Beccy Shipman |
Date Deposited: | 11 Feb 2009 17:41 |
Last Modified: | 08 Feb 2013 16:57 |
Published Version: | http://dx.doi.org/10.1080/08927020500134177 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/08927020500134177 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:7691 |