Showing 5 open source projects for "windows development"

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    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...
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  • 2
    We developed a systematic algorithmic solution for quantitative drug sensitivity scoring (DSS), based on continuous modeling and integration of multiple dose-response relationships in high-throughput compound testing studies. License: The DSS R-package is made available under the terms of the GNU General Public License, which means that the source code is freely available for use within other software, but if you alter the code and distribute it, you must make the new source code...
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  • 3
    An open-source implementation of our network-based target deconvolution approach, named target addiction score (TAS). License: The TAS R-package is made available under the terms of the GNU General Public License, which means that the source code is freely available for use within other software, but if you alter the code and distribute it, you must make the new source code freely available as well. This software is distributed in the hope that it will be useful, but WITHOUT ANY...
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  • 4
    Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator
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    clusterCons
    An R package implementation of a consensus clustering methodology. This package allows users to perform re-sampling statistics based clustering using multiple clustering algorithms to assess the robustness of both clusters and members of clusters.
    Downloads: 1 This Week
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