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      Open source clustering software.

      Bioinformatics (Oxford, England)
      Oxford University Press (OUP)

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          Abstract

          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.

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          Journal
          14871861
          10.1093/bioinformatics/bth078

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