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Updated: Aug 4, 2026

Spatial Separation of Molecular Conformers and Clusters
Published on: January 9, 2014
Fuzzy clustering as a means of selecting representative conformers and molecular alignments
Miklos Feher1, Jonathan M Schmidt
1SignalGene Inc., 2-335 Laird Road, Guelph, Ontario, N1G 4P7, Canada. miklos.feger@signalgene.com
Abstract:
This paper describes the first application of fuzzy c-means clustering for the selection of representatives from assemblies of conformations or alignments. In case of alignments, their quality is taken into account using a weighted c-means scheme, developed in this work. The performance of fuzzy cluster validity measures, such as compactness, partition function, and entropy, are studied on several examples, but the visual 3D representation of data points is shown to be most beneficial in determining the optimum number of clusters. Fuzzy clustering is expected to perform better than crisp clustering methods in cases where there are a significant number of "outliers", such as in molecular dynamics simulations and molecular alignments.
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