Showing 12 open source projects for "data capture framework"

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  • 1
    bioweb

    bioweb

    polyglot language framework to analyze genetic data

    polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences
    Downloads: 2 This Week
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  • 2
    An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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    Downloads: 11 This Week
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  • 3
    Copy Number Analysis for Targeted Resequencing (CONTRA) is a tool for copy number variation (CNV) detection for targeted resequencing data such as those from whole-exome capture data.
    Downloads: 8 This Week
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  • 4
    scipion-xmipp

    scipion-xmipp

    Image processing framework to integrate EM software packages.

    Scipion is an image processing framework to obtain 3D models of macromolecular complexes using Electron Microscopy (3DEM). It integrates several software packages and presents an unified interface for both biologists and developers. Scipion allows to execute workflows combining different software tools, while taking care of formats and conversions. Additionally, all steps are tracked and can be reproduced later on. Xmipp is a well-known package in the EM image processing. It is integrated...
    Downloads: 0 This Week
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  • 5

    pipasic

    pipasic: Protein Abundance Correction in Metaproteomic Data

    Metaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise due to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in...
    Downloads: 0 This Week
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  • 6
    pyMantis
    pyMantis is a data-management system for (systems) biology build on the web2py framework. It features: tree based file explorer, relational db table wizzard with automated creation of user interfaces, internal and external access management, wiki, ..
    Downloads: 0 This Week
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  • 7
    GEPETTO - Gene Prioritization in Java

    GEPETTO - Gene Prioritization in Java

    GEPETTO (GEne Prioritization ExTended TOol)

    GEPETTO (GEne PrioriTization ExTended TOol) is an original open-source framework, distributed under the LGPL license, for gene selection and prioritization on a desktop computer that ensures confidentiality of personal data. It takes advantage of the data integration capabilities in the SM2PH-Central Framework(KD4v,MSV3d,BIRD,..), combined with in-house developed gene prioritization methods. It currently incorporates six prioritization modules, based on gene sequence, protein-protein interactions, gene expression, disease-causing probabilities, genomic context). ...
    Downloads: 1 This Week
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  • 8
    CoNIFER

    CoNIFER

    Homepage for CoNIFER (Copy Number Inference From Exome Reads)

    CoNIFER uses exome sequencing data to find copy number variants (CNVs) and genotype the copy-number of duplicated genes.
    Downloads: 1 This Week
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  • 9
    Python module for manipulation of Crystallographic Information Framework (CIF) files
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    Downloads: 0 This Week
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  • 10
    A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.
    Downloads: 0 This Week
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  • 11
    MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).
    Downloads: 0 This Week
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  • 12
    A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining
    Downloads: 0 This Week
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