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 0095-2338Full text not available from this repository.
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.
|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)
|Depositing User:||Information Studies|
|Date Deposited:||24 Mar 2009 12:57|
|Last Modified:||13 May 2009 18:07|
|Publisher:||American Chemical Society|