Chen, B., Mueller, C. and Willett, P. (2009) Evaluation of a Bayesian inference network for ligand-based virtual screening. Cheminformatics, 1 (5). ISSN 1758-2946
Abstract
Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity.
Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought.
Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2009 Chen et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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 > 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: | Miss Anthea Tucker |
Date Deposited: | 28 Sep 2009 15:37 |
Last Modified: | 05 Jun 2014 03:41 |
Published Version: | http://dx.doi.org/10.1186/1758-2946-1-5 |
Status: | Published |
Publisher: | Chemistry Central |
Refereed: | Yes |
Identification Number: | 10.1186/1758-2946-1-5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:9788 |