Showing 6 open source projects for "data visualization"

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  • 1
    PANDA

    PANDA

    A comprehensive and flexible quantification tool for proteomics data

    PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels...
    Downloads: 0 This Week
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  • 2

    Waterloo

    Java-based scientific graphics

    Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.
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  • 3
    HeatmapGenerator
    HeatmapGenerator is a graphical user interface software program written in C++, R, and OpenGL to create customized gene expression heatmaps from RNA-seq and microarray data in medical research. HeatmapGenerator can also be used to make heatmaps in a variety of other non-medical fields. HeatmapGenerator is peer-reviewed published software (http://www.scfbm.org/content/9/1/30). Please cite: [Khomtchouk et al.: "HeatmapGenerator: High performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline." ...
    Downloads: 1 This Week
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  • 4
    Django-dataplot enables developers using the Django web framework to seamlessly integrate data-driven graphical plots into their web pages.
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  • 5
    Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.
    Downloads: 0 This Week
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  • 6
    RGnome is a gtk based frontend for GNU R, which is a widely used language for statistical computing. It features a fully working R console and an editor with syntax highlighting.
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