| Autor: |
D. Holliday, John, L. Rodgers, Sarah, Willett, Peter, Chen, Min-You, Mahfouf, Mahdi, Lawson, Kevin, Mullier, Graham |
| Zdroj: |
Journal of Chemical Information and Modeling; May 2004, Vol. 44 Issue: 3 p894-902, 9p |
| 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: |
Supplemental Index |
| Externí odkaz: |
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