{
    "info": {
        "author": "Christian Diener",
        "author_email": "mail@cdiener.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
        ],
        "description": "|travis| |appveyor| |codecov.io| |Code Health|\n\nCORDA for Python\n================\n\nThis is a Python implementation based on the papers of Schultz et. al. with\nsome added optimizations. It is based on the following two publiactions:\n\n- `Reconstruction of Tissue-Specific Metabolic Networks Using\n  CORDA <http://journals.plos.org/ploscompbiol/article/authors?id=10.1371%2Fjournal.pcbi.1004808>`_\n- `IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS\n  <http://dx.doi.org/10.1142/9789813207813_0045>`_\n\nThis Python package is developed in the\n`Human Systems Biology Group <https://resendislab.github.io>`_ of\nProf. Osbaldo Resendis Antonio at the `National Institute of Genomic\nMedicine Mexico <https://inmegen.gob.mx>`_ and includes recent updates to\nthe method (*CORDA 2*).\n\n\nHow to cite?\n------------\n\nThis particular implementation of CORDA has not been published so far. In the\nmeantime you should if you cite the respective publications for the method\nmentioned above and provide a link to this GitHub repository.\n\nWhat does it do?\n----------------\n\nCORDA, short for Cost Optimization Reaction Dependency Assessment is a\nmethod for the reconstruction of metabolic networks from a given\nreference model (a database of all known reactions) and a confidence\nmapping for reactions. It allows you to reconstruct metabolic models for\ntissues, patients or specific experimental conditions from a set of\ntranscription or proteome measurements.\n\nHow do I install it\n-------------------\n\nCORDA for Python works only for Python 3.4+ and requires\n`cobrapy <http://github.com/opencobra/cobrapy>`__ to work. After having\na working Python installation with pip (Anaconda or Miniconda works fine\nhere as well) you can install corda with pip\n\n.. code:: bash\n\n    pip install corda\n\nThis will download and install cobrapy as well. I recommend using a\nversion of pip that supports manylinux builds for faster installation\n(pip>=8.1).\n\nFor now the master branch is usually working and tested whereas all new\nfeatures are kept in its own branch. To install from the master branch\ndirectly use\n\n.. code:: bash\n\n    pip install https://github.com/resendislab/corda/archive/master.zip\n\nWhat do I need to run it?\n-------------------------\n\nCORDA requires a base model including all reactions that could possibly\nincluded such as Recon 1/2 or HMR. You will also need gene expression or\nproteome data for our tissue/patient/experimental setting. This data has\nto be translated into 5 distinct classes: unknown (0), not\nexpressed/present (-1), low confidence (1), medium confidence (2) and\nhigh confidence (3). CORDA will then ensure to include as many high\nconfidence reactions as possible while minimizing the inclusion of\nabsent (-1) reactions while maintaining a set of metabolic requirements.\n\nHow do I use it?\n----------------\n\nA small tutorial is found at https://resendislab.github.io/corda.\n\nWhat's the advantage over other reconstruction algorithms?\n----------------------------------------------------------\n\nNo commercial solver needed\n***************************\n\nIt does not require any commercial solvers, in fact it works fastest\nwith the free glpk solver that already comes together with cobrapy.\nFor instance for the small central metabolism model (101 irreversible\nreactions) included together with CORDA the glpk version is a bout 3 times\nfaster than the fastest tested commercial solver (cplex).\n\nFast reconstructions\n********************\n\nCORDA for Python uses a strategy similar to FastFVA, where\na previous solution basis is recycled repeatedly.\n\nSome reference times for reconstructing the minimal growing models for\niJO1366 (*E. coli*) and Recon 2.2:\n\n.. code:: python\n\n    In [1]: from cobra.test import create_test_model\n    Loading symengine... This feature is in beta testing. Please report any issues you encounter on http://github.com/biosustain/optlang/issues\n\n    In [2]: from cobra.io import read_sbml_model\n\n    In [3]: from corda import CORDA\n\n    In [4]: ecoli = create_test_model(\"ecoli\")\n\n    In [5]: conf = {}\n\n    In [6]: for r in ecoli.reactions:\n    ...:     conf[r.id] = -1\n    ...:\n\n    In [7]: conf[\"Ec_biomass_iJO1366_core_53p95M\"] = 3\n\n    In [8]: %time opt = CORDA(ecoli, conf)\n    CPU times: user 282 ms, sys: 1.81 ms, total: 284 ms\n    Wall time: 284 ms\n\n    In [9]: %time opt.build()\n    CPU times: user 9.04 s, sys: 93 \u00b5s, total: 9.04 s\n    Wall time: 9.05 s\n\n    In [10]: print(opt)\n    build status: reconstruction complete\n    Inc. reactions: 456/2583\n    - unclear: 0/0\n    - exclude: 455/2582\n    - low and medium: 0/0\n    - high: 1/1\n\n\n    In [11]:\n\n    In [12]: recon2 = read_sbml_model(\"/home/cdiener/Downloads/recon_2.2.xml\")\n    cobra/io/sbml.py:235 UserWarning: M_h_c appears as a reactant and product RE3453C\n    cobra/io/sbml.py:235 UserWarning: M_h_c appears as a reactant and product RE3459C\n    cobra/io/sbml.py:235 UserWarning: M_h_x appears as a reactant and product FAOXC24C22x\n    cobra/io/sbml.py:235 UserWarning: M_h_c appears as a reactant and product HAS1\n    cobra/io/sbml.py:235 UserWarning: M_h2o_x appears as a reactant and product PROFVSCOAhc\n\n    In [13]: conf = {}\n\n    In [14]: for r in recon2.reactions:\n        ...:     conf[r.id] = -1\n        ...:\n\n    In [15]: conf[\"biomass_reaction\"] = 3\n\n    In [16]: %time opt = CORDA(recon2, conf)\n    CPU times: user 1 s, sys: 8.95 ms, total: 1.01 s\n    Wall time: 1.01 s\n\n    In [17]: %time opt.build()\n    CPU times: user 24.7 s, sys: 240 \u00b5s, total: 24.7 s\n    Wall time: 24.8 s\n\n    In [28]: print(opt)\n    build status: reconstruction complete\n    Inc. reactions: 395/7864\n    - unclear: 0/0\n    - exclude: 394/7863\n    - low and medium: 0/0\n    - high: 1/1\n\n.. |travis| image:: https://travis-ci.org/resendislab/corda.svg?branch=master\n   :target: https://travis-ci.org/resendislab/corda\n.. |appveyor| image:: https://ci.appveyor.com/api/projects/status/vr0ibaiqb5lnu3ii/branch/master?svg=true\n   :target: https://ci.appveyor.com/project/cdiener/corda-69at9/branch/master\n.. |codecov.io| image:: https://codecov.io/github/resendislab/corda/coverage.svg?branch=master\n   :target: https://codecov.io/github/resendislab/corda?branch=master\n.. |Code Health| image:: https://landscape.io/github/resendislab/corda/master/landscape.svg?style=flat\n   :target: https://landscape.io/github/resendislab/corda/master\n\n\n",
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        "keywords": "biology metabolism reconstruction cobra",
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        "maintainer": "",
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