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Combination of molecular similarity measures using data fusion

Ginn, C.M.R., Willett, P. and Bradshaw, J. (2000) Combination of molecular similarity measures using data fusion. Perspectives in Drug Discovery and Design, 20 (1). pp. 1-16. ISSN 1573 - 9023

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Abstract

Many different measures of structural similarity have been suggested for matching chemical structures, each such measure focusing upon some particular type of molecular characteristic. The multi-faceted nature of biological activity suggests that an appropriate similarity measure should encompass many different types of characteristic, and this article discusses the use of data fusion methods to combine the results of searches based on multiple similarity measures. Experiments with several different types of dataset and activity suggest that data fusion provides a simple, but effective, approach to the combination of individual similarity measures. The best results were generally obtained with a fusion rule that sums the rank positions achieved by each molecule in searches using individual measures.

Item Type: Article
Copyright, Publisher and Additional Information: © 2000 Springer. This is an author produced version of a paper published in Perspectives in Drug Discovery and Design. Uploaded in accordance with the publisher's self-archiving policy.
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Sherpa Assistant
Date Deposited: 11 Jan 2008 15:55
Last Modified: 08 Feb 2013 16:55
Published Version: http://dx.doi.org/10.1023/A:1008752200506
Status: Published
Publisher: Springer
Refereed: Yes
Identification Number: 10.1023/A:1008752200506
URI: http://eprints.whiterose.ac.uk/id/eprint/3575

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