Holliday, J.D., Rodgers, S.L., Willett, P. et al. (4 more authors) (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
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.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Dates: |
|
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 |
Published Version: | http://dx.doi.org/10.1021/ci0342674 |
Status: | Published |
Publisher: | American Chemical Society |
Refereed: | Yes |
Identification Number: | 10.1021/ci0342674 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:8113 |