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Clustering files of chemical structures using the fuzzy k-means clustering method

Holliday, J.D., Rodgers, S.L., Willett, P., Chen, M-Y., Mahfouf, M., Lawson, K. and Mullier, G. (2004) Clustering files of chemical structures using the fuzzy k-means clustering method. Journal of Chemical Information and Computer Sciences, 44 (3). pp. 894-902. ISSN 0095-2338

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Abstract

This paper evaluates the use of the fuzzy k-means clustering method for the clustering of files of 2D chemical structures. Simulated property prediction experiments with the Starlist file of logP values demonstrate that use of the fuzzy k-means method can, in some cases, yield results that are superior to those obtained with the conventional k-means method and with Ward's clustering method. Clustering of several small sets of agrochemical compounds demonstrate the ability of the fuzzy k-means method to highlight multicluster membership and to identify outlier compounds, although the former can be difficult to interpret in some cases.

Item Type: Article
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)
Depositing User: Information Studies
Date Deposited: 24 Mar 2009 12:57
Last Modified: 13 May 2009 18:07
Published Version: http://dx.doi.org/10.1021/ci0342674
Status: Published
Publisher: American Chemical Society
Refereed: Yes
Identification Number: 10.1021/ci0342674
URI: http://eprints.whiterose.ac.uk/id/eprint/8113

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