Bioinformatics Advance Access published online on February 10, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth078
Bioinformatics © Oxford University Press 2004; all rights reserved
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1 Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
* To whom correspondence should be addressed. E-mail: mdehoon{at}ims.u-tokyo.ac.jp.
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. Software 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.
Revised July 27, 2003
Accepted July 31, 2003
Applications note
Open source clustering software
2 University of California, Santa Cruz Extension in Silicon Valley, 10420 Bubb Road, Cupertino, CA 95014, USA
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