Implement the commonly used clustering methods to analyze gene expression data. Select the materials to process and apply one or several of the available tools. Check and customize the layouts of the user interface, manage the data, save changes, view logs, etc.
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The open source clustering software implement's the most commonly used clustering methods for gene expression data analysis. The clustering methods can be used in several ways. Cluster provides a Graphical User Interface to access to the clustering routines. It is available for Windows, Mac OS X, and Linux/Unix. Python users can access the clustering routines by using Pycluster, which is an extension module to Python. People that want to make use of the clustering algorithms in their own C, C , or Fortran programs can download the source code of the C Clustering Library.