Showing 5 open source projects for "python time series analysis"

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  • 1
    The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.
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    Downloads: 32 This Week
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  • 2

    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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  • 3

    BioDare

    BioDare is Biological Data Repository focused on timeseries data

    BioDare (Biological Data Repository) was developed under the multi-site ROBuST project (http://hallidaylab.bio.ed.ac.uk/ROBuST.html) to support data exchange inside the project. It is a web application which allows data-sharing (including public dissemination), data-processing and analysis, with the main focus on time-series data produced in circadian experiments. The main features of BioDare are: - an online repository for experimental data accompanied by extensive metadata - generation of secondary data (normalized, detrended, averaged …) - graphical output of data, secondary data and rhythm analysis - simple text-based search throughout metadata - biology- and conditions-aware search for data - data aggregation and export - group-based privacy settings for collaborative research
    Downloads: 0 This Week
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  • 4
    GeneNetWeaver
    GeneNetWeaver (GNW) is an open-source tool for in silico benchmark generation and performance profiling of network inference methods. GNW was used to generate the community-wide DREAM3, DREAM4 and DREAM5 In Silico Challenges.
    Downloads: 6 This Week
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  • 5
    XMAS supports a new kind of “sit forward” time series microarray analysis through visual interaction and interoperable operators. Domain knowledge is integrated directly into the system to aid users in their analysis.
    Downloads: 0 This Week
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