Metadata-Version: 1.1
Name: bio-APRICOT
Version: 1.1.3
Summary: Sequence-based identification and characterization of protein classes
Home-page: https://www.python.org/pypi/bio-apricot
Author: Malvika Sharan
Author-email: malvikasharan@gmail.com
License: ISC License (ISCL)
Description: .. image:: https://zenodo.org/badge/21283/malvikasharan/APRICOT.svg
           :target: https://zenodo.org/badge/latestdoi/21283/malvikasharan/APRICOT
          
        APRICOT
        -------
        
        A tool for sequence-based identification and characterization of protein classes
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        `APRICOT`_ is a computational pipeline for the identification of
        specific functional classes of interest in large protein sets. The
        pipeline uses efficient sequence-based algorithms and predictive models
        like signature motifs of protein families for the characterization of
        user-provided query proteins with specific functional features. The
        dynamic framework of APRICOT allows the identification of unexplored
        functional classes of interest in the large protein sets or the entire
        proteome.
        
        Authors and Contributors
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
        The tool is designed and developed by Malvika Sharan in
        the lab of Prof. Dr. Jörg Vogel and Dr. Ana Eulalio in the Institute for
        Molecular Infection Biology at the University of Würzburg. Dr. Konrad
        Förstner contributed to the project by providing important
        technical supervision and discussions. The authors are grateful to
        Prof. Thomas dandekar, Dr. Charlotte Michaux, Caroline Taouk and
        Dr. Lars Barquist for critical discussions and feedback.
        
        Source code
        ~~~~~~~~~~~
        
        The source codes of APRICOT are available via git
        https://github.com/malvikasharan/APRICOT and pypi
        https://pypi.python.org/pypi/bio-apricot.
        
        License
        -------
        
        APRICOT is open source software and is available under the ISC license.
        
        Copyright (c) 2011-2015, Malvika Sharan, malvika.sharan@uni-wuerzburg.de
        
        Please read the license content `here`_.
        
        Installation
        ------------
        
        1. Python packages required for APRICOT can be installed with pip
        
        ::
        
            $ pip install bio-apricot
            
        
        Or update the package list manually: sudo apt-get update and install the required packages (sudo apt-get install python3-matplotlib python3-numpy python3-scipy python3-biopython python3-requests python3-openpyxl).
        
        2. The scripts for the installaton of the different componenents of APRICOT
        (databases, tools and flatfiles) are available on the GitHub repository.
        You can manually download the APRICOT repository or simply clone it.
        
        ::
        
            $ git clone https://github.com/malvikasharan/APRICOT.git
        
        The `Docker image for APRICOT`_ will be available soon.
        
        The shell script to install and run the analysis in a streamlined manner
        is provided with the package (`see here`_).
        
        Working example
        ---------------
        
        We recomend you to check out the `tutorial`_ that discusses each module
        of APRICOT in detail. The repository contains a shell script
        `run\_example.sh`_, which can be used for the demonstration of APRICOT
        analysis with an example.
        
        In the packages we have provided a test folder named `tests`_,
        to allow the system testing. The instructions and commands are provided
        in the shell scipt `system\_test.sh`_.
        
        Users can choose to install all the tools and databases for a complete
        test. Optionally, the `test datasets`_ can be used for basic testing,
        which does not require installation of third party tools.
        
        Contact
        -------
        
        For question, troubleshooting and requests, please feel free to contact
        Malvika Sharan at malvika.sharan@uni-wuerzburg.de
        
        .. _APRICOT: http://malvikasharan.github.io/APRICOT/
        .. _here: https://github.com/malvikasharan/APRICOT/blob/master/LICENSE.md
        .. _Docker image for APRICOT: https://github.com/malvikasharan/APRICOT/blob/master/Dockerfile
        .. _see here: https://github.com/malvikasharan/APRICOT/blob/master/system_test.sh
        .. _tutorial: https://github.com/malvikasharan/APRICOT/blob/master/APRICOT_tutorial.md
        .. _run\_example.sh: https://github.com/malvikasharan/APRICOT/blob/master/shell_scripts/run_example.sh
        .. _tests: https://github.com/malvikasharan/APRICOT/tree/master/tests
        .. _system\_test.sh: https://github.com/malvikasharan/APRICOT/blob/master/tests/system_test.sh
        .. _test datasets: https://github.com/malvikasharan/APRICOT/tree/master/tests/demo_files_small
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: ISC License (ISCL)
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
