7 projects for "cluster analysis" with 2 filters applied:

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  • 1

    Deem

    Analyze time-course data with significance tests, clustering, modeling

    Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional...
    Downloads: 0 This Week
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  • 2
    AWclust is easy to use non-parametric population structure analysis software written for R with a GUI interface. Just point and click and you will be on your way to discovering the important cluster information in your SNP data sets.
    Downloads: 0 This Week
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  • 3
    IMPORTANT: The project moved over to github! You can find it at: https://github.com/exhuma/python-cluster
    Downloads: 0 This Week
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  • 4

    QSAS plug-ins

    Plug-ins for the space physics data analysis software QSAS.

    The project is concerned with developing new plug-ins for the space plasma analysis software QSAS. The plug-ins are developed mainly for the Cluster II mission, Champ and Swarm. QSAS can be downloaded from: http://www.sp.ph.ic.ac.uk/csc-web/QSAS/
    Downloads: 0 This Week
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  • 5
    Facelift is a visualization and analysis software for online social networking services. It displays a given community as a node-link diagram and provides several search / filtering functions as well as cluster analysis features.
    Downloads: 0 This Week
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  • 6
    The CHIP Cluster Generator attempts to create spatio-temporal cluster data in an automated fashion to help evaluate epidemic detection software. The spatio-temporal data will then be used to determine robustness of spatial detection algorithms.
    Downloads: 0 This Week
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  • 7
    clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.
    Downloads: 0 This Week
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