| Autor: |
Holliday JD; Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield S10 2TN, U.K., Rodgers SL, Willett P, Chen MY, Mahfouf M, Lawson K, Mullier G |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of chemical information and computer sciences [J Chem Inf Comput Sci] 2004 May-Jun; Vol. 44 (3), pp. 894-902. |
| DOI: |
10.1021/ci0342674 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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