Open Source S/R Data Management Systems for Linux

S/R Data Management Systems for Linux

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Browse free open source S/R Data Management Systems for Linux and projects below. Use the toggles on the left to filter open source S/R Data Management Systems for Linux by OS, license, language, programming language, and project status.

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  • 1
    Django-dataplot enables developers using the Django web framework to seamlessly integrate data-driven graphical plots into their web pages.
    Downloads: 0 This Week
    Last Update:
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  • 2

    Electrophysiology & circular stats tools

    Data analysis and circular statistics with OpenElectrophy and R

    Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem. This packages may be useful for people who start using OpenElectrophy and circular statistics in R. If you find errors, please report them. The project is still in development, so in the future you'll get updates.
    Downloads: 0 This Week
    Last Update:
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  • 3
    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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  • 4

    Waterloo

    Java-based scientific graphics

    Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.
    Downloads: 0 This Week
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  • Create and run cloud-based virtual machines. Icon
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    Secure and customizable compute service that lets you create and run virtual machines.

    Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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  • 5

    iMir

    Integrated pipeline for HT miRNA-Seq data analysis

    Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs.
    Downloads: 0 This Week
    Last Update:
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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.
    Downloads: 0 This Week
    Last Update:
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