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Bioinformatics Advance Access originally published online on February 10, 2004
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Bioinformatics 20(9) © Oxford University Press 2004; all rights reserved.

Applications Note

Open source clustering software

M.J.L. de Hoon 1,*, S. Imoto 1, J. Nolan 2 and S. Miyano 1

1 Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan and 2 University of California, Santa Cruz Extension in Silicon Valley, 10420 Bubb Road, Cupertino, CA 95014, USA

Received on June 17, 2003; revised on July 27, 2003; accepted on July 31, 2003
Advance Access Publication February 10, 2004

Summary: We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C.

Availability: The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

Contact: mdehoon{at}ims.u-tokyo.ac.jp

* To whom correspondence should be addressed.


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