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The open source clustering software available here contains clustering
routines that can be used to analyze gene expression data. Routines
for hierarchical (pairwise simple, complete, average, and centroid
linkage) clustering, k-means and k-medians clustering,
and 2D self-organizing maps are included. The routines are available
in the form of a C clustering library,
an extension module to Python, a module
to Perl,
as well as an enhanced version of Cluster,
which was originally developed by Michael
Eisen of Berkeley Lab. The
C clustering library and the associated extension module for
Python was released under the Python license. The Perl module was
released under the Artistic License.
Cluster 3.0 is covered by the
original
Cluster/TreeView license.
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Laboratory of DNA Information Analysis Human Genome CenterInstitute of Medical Science University of Tokyo |
© 2002, Michiel de Hoon,
All rights reserved.
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