Metadata-Version: 2.1
Name: farseernmr
Version: 2.0.0.dev0
Summary: A software suite for automatic treatment, analysis and plotting of large and multivariable datasets of bioNMR peaklists.
Home-page: https://github.com/Farseer-NMR/FarSeer-NMR
Author: FarSeer-NMR
Author-email: farseer.nmr@gmail.com
License: GNU GPLv3+
Project-URL: Documentation, https://farseernmr.readthedocs.io/
Project-URL: Changelog, https://farseernmr.readthedocs.io/en/latest/changelog.html
Project-URL: Issue Tracker, https://github.com/FarSeer-NMR/FarSeer-NMR/issues
Description: .. start-readme
        
        ===========
        FarSeer-NMR
        ===========
        
        .. image:: https://raw.githubusercontent.com/Farseer-NMR/FarSeer-NMR/master/docs/img/GitHub-FS_logo_version2_small.png
        
        **Attention Attention Attention**
        
        We are currently rewriting Farseer-NMR towards **version 2**.  
        
        **Version 1** is still functional and working, though not much supported apart from minor bugs. You can download the latest stable version, v1.3.5, on the `releases tab <https://github.com/Farseer-NMR/FarSeer-NMR/releases/tag/v1.3.5>`_, or visit the complete version 1 code and its documentation in `version 1 branch <https://github.com/Farseer-NMR/FarSeer-NMR/tree/version1>`_) on GitHub.
        
        Our original publication is available at `JBioMolNMR <https://link.springer.com/article/10.1007/s10858-018-0182-5>`_), cite us if you use Farseer-NMR for your research, regardless of which version you use.
        
        Please note that the `master branch <https://github.com/Farseer-NMR/FarSeer-NMR>`_) currently hosts the development of version 2, which is UNFINISHED software; again, please, refer to *version 1* for a stable and functional release.
        
        Farseer-NMR runs purely on volunteer work without any official assigned funds. All help is welcomed, `engage with us <https://groups.google.com/forum/#!forum/farseer-nmr>`_)!
        
        **Attention Attention Attention**
        
        .. image:: https://raw.githubusercontent.com/Farseer-NMR/FarSeer-NMR/master/docs/img/GitHub_Farseer-NMR_Workflow.png
        
        A Python written, multi-platform and fully community-driven suite to analyse datasets of **peaklist files** extracted from multivariable series of Biomolecular Nuclear Magnetic Resonance (NMR) experiments. 
        
        With Farseer-NMR, you have:
        
        * Automatic analysis of large and multivariable NMR **peaklist files** datasets
        * Peaklist parsing and treatment
        * Identification of _missing_ and _unassigned_ residues
        * Automatic calculation of NMR parameters
        * Comprehensive organization of the output
        * Large suite of publication-ready plotting templates
        * Full traceability via `Markdown <https://en.wikipedia.org/wiki/Markdown>`_) formatted log file.
        
        .. end-readme
        
        Download, Install and Update
        ============================
        
        `Download here the latest version of Farseer-NMR. <https://github.com/Farseer-NMR/FarSeer-NMR/releases>`_.
        
        To install Farseer-NMR simply run the installation script::
        
            python install_farseernmr.py
        
        Read `here <https://github.com/Farseer-NMR/FarSeer-NMR/wiki/Download,-Install-and-Update>`_ some additional detail on how to setup your Farseer-NMR installation - it's very easy!
        
        Documentation
        =============
        
        The complete Farseer-NMR documentation is available on our `Wiki page <https://github.com/Farseer-NMR/FarSeer-NMR/wiki>`_.
        
        Participate in the Farseer-NMR development
        ==========================================
        
        To contribute to the development of Farseer-NMR `visit our GitHub project <https://github.com/Farseer-NMR/FarSeer-NMR>`_). If you are a user, share your experience in the issues tab (reporting bugs, suggestions or discussions); if you are a developer read our `CONTRIBUTING <https://github.com/Farseer-NMR/FarSeer-NMR/blob/master/CONTRIBUTING.md>`_) guidelines. 
        
        Social Media
        ============
        
        - Post on our `mailing list <https://groups.google.com/forum/#!forum/farseer-nmr>`_) for questions, discussion and help!
        - Follow us on Twitter `@farseer_nmr <https://twitter.com/farseer_nmr>`_)
        - Find us on `Research Gate <https://www.researchgate.net/project/Farseer-NMR-automatic-treatment-and-plotting-of-large-scale-NMR-titration-data>`_), where our seminars PDFs are available!
        
        
        .. start-citing
        
        Citing
        ======
        
        Thanks for using Farseer-NMR!
        
        If you are using Farseer-NMR, or any of its components, to analyze your NMR peaklist data, **please cite our original article**:
        
        Teixeira, J.M.C., Skinner, S.P., Arbesú, M., Breeze, A.L., Pons, M. **J Biomol NMR** (2018) 71:1, 1-9. DOI `10.1007/s10858-018-0182-5 <https://link.springer.com/article/10.1007/s10858-018-0182-5>`_)
        
        Publications citing Farseer-NMR
        -------------------------------
        
        * Miguel Arbesú, MiquelPons. Integrating disorder in globular multidomain proteins: Fuzzy sensors and the role of SH3 domains. Archives of Biochemistry and Biophysics 2019, 677, 108161 `https://doi.org/10.1016/j.abb.2019.108161 <https://www.sciencedirect.com/science/article/abs/pii/S0003986119305922>`_.
        * Luca Mureddu, Geerten W. Vuister. Simple high‐resolution NMR spectroscopy as a tool in molecular biology. The FEBS Journal 2019, 286, issue 11, p2035 `https://doi.org/10.1111/febs.14771 <https://febs.onlinelibrary.wiley.com/doi/full/10.1111/febs.14771>`_.
        * Teixeira, J.M.C.; Fuentes, H.; Bielskutė, S.; Gairi, M.; Żerko, S.; Koźmiński, W.; Pons, M. The Two Isoforms of Lyn Display Different Intramolecular Fuzzy Complexes with the SH3 Domain. Molecules 2018, 23, 2731. `https://doi.org/10.3390/molecules23112731 <https://www.mdpi.com/1420-3049/23/11/2731>`_)
        * Arbesú, M.; Iruela, G.; Fuentes, H.; Teixeira, J.M.C.; Pons, M. Intramolecular fuzzy interactions involving intrinsically disordered domains. Front. Mol. Biosci. 2018, 5, 39. `DOI 10.3389/fmolb.2018.00039 <https://www.frontiersin.org/articles/10.3389/fmolb.2018.00039/full>`_)
        * Arbesú, M. et al. (2017) The Unique Domain Forms a Fuzzy Intramolecular Complex in Src Family Kinases. Structure 25, 630–640.e4. `10.1016/j.str.2017.02.011 <https://www.ncbi.nlm.nih.gov/pubmed/28319009>`_)
        * Marimon, O. et. al. (2016). An oxygen-sensitive toxin–antitoxin system. Nature Communications, 7, 13634. `https://doi.org/10.1038/ncomms13634 <https://www.nature.com/articles/ncomms13634>`_)
        * Bijlmakers, M.-J., et.al. (2015) A C2HC zinc finger is essential for the RING-E2 interaction of the ubiquitin ligase RNF125. Scientific Reports, 6, 29232. `https://doi.org/10.1038/srep29232 <https://www.nature.com/articles/srep29232>`_)
        
        `Farseer-NMR on Google Citations <https://scholar.google.com/scholar?oi=bibs&hl=en&cites=2639623686400809983>`_)
        .. end-citing
        .. start-acknowledge
        
        Acknowledgments
        ===============
        
        The Farseer-NMR Project wants to acknowledge to following people for their contributions to the project:
        
        - Susana Barrera-Vilarmau ([ORCID 0000-0003-4868-6593](https://orcid.org/0000-0003-4868-6593)): beta-tester, data provider, plot suggestions.
        - Jamie Ferrar, [Artistic Systems](https://twitter.com/artisticsystems): for providing the UI branding.
        - [João P.G.L.M. Rodrigues](https://github.com/JoaoRodrigues): for all the years of coding discussions and mentorship, and in particular for the help in setting the Farseer-NMR organization profile on GitHub.
        - Héctor Fuentes: intensive beta-tester, specially for the Windows version.
        - To all the users and participants of the Farseer-NMR workshops, thanks for your feedback, opinions, testing, interest and patience. Your contribution is definitively making Farseer-NMR growing bigger and robust! Special thanks to:
            - [Micael Silva (Nova University of Lisbon)](https://www.researchgate.net/profile/Micael_Silva)
            - [Wouter Elings (Leiden University)](https://www.universiteitleiden.nl/en/staffmembers/wouter-elings#tab-1)
        
        .. end-acknowledge
        .. start-license
        
        License
        =======
        
        The entire Farseer-NMR project is distributed with no liability and is licensed under the `GPL-3.0 <https://github.com/Farseer-NMR/FarSeer-NMR/blob/master/COPYING>`_.
        
        <a href="https://www.gnu.org/licenses/gpl-3.0.en.html"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/9/93/GPLv3_Logo.svg/1200px-GPLv3_Logo.svg.png" width="75" height="37"></a>
        
        .. end-license
        
        Versioning
        ==========
        
        This project follows strictly `Semantic Versioning 2.0 <https://semver.org/#semantic-versioning-200>`_ for version control. 
        
        
        Changelog
        =========
        
        v2
        --
        
        * *under development*
        * added configuration files for CI and deployment
        * configured tox.ini
        * configured Travis-CI multiplaform, multi Python CI #316
        
        v1
        --
        
        * For list of v1 releases visit `project releases <https://github.com/Farseer-NMR/FarSeer-NMR/releases>`_.
        * Latest v1 release hosted in `version1 <https://github.com/Farseer-NMR/FarSeer-NMR/tree/version1>`_ branch.
        
        v0
        --
        
        * pre-publication no JBioNMR, changes not tracked in detail.
        
Keywords: Proteins,DNA,RNA,Structural Biology,Molecular Biology,Biochemistry,Nuclear Magnetic Resonance
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Environment :: Console
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Utilities
Requires-Python: >=3.6, <=3.9
Provides-Extra: sup
