[gmx-users] clustering and representative structure
sgourn at rpi.edu
Sun Feb 4 18:51:00 CET 2007
The most cited method on clustering is probably k-means. Although not
included in the current gromacs version, I have implemented it within
the gromacs gmx_cluster code and you can find it in the archives.
All of these methods (excluding principal components) can offer central
actual structures that are representative of your sample. Since there is
no "best" clustering but the output depends strongly on the distribution
of structures in your dataset, no method is guaranteed to find the most
representative structures. However, you can obtain a consensus of
structural features, through a comparison of the central structures from
A very good reference on clustering is the book by J.A. Hartigan
Carlos Javier Nuñez Aguero wrote:
> Hi all,
> How are you?
> In Gromacs, the clustering methods are:
> o Full linkage
> o Jarvis Patrick
> o Monte Carlo
> o Diagonalization, and
> o Gromos
> ---- what is the most cited method?
> ---- what option generate "the most representative structure"?
> all the strategies? why?
> (not the average geometry)
> ---- where I can read more (or where I can find specific information)
> about of
> every methodology of clustering?
> links, papers, etc? (moreover of the manual or online or html
> Carlos Javier
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Nikolaos G. Sgourakis, MSc
Center for Biotechnology and Interdisciplinary studies
Troy, NY 12180
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