Clustering files of chemical structures using the fuzzy k-means clustering method |
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Authors: | Holliday John D Rodgers Sarah L Willett Peter Chen Min-You Mahfouf Mahdi Lawson Kevin Mullier Graham |
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Institution: | Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield S10 2TN, U.K. |
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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. |
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