gMCSpy


NamegMCSpy JSON
Version 1.0.1 PyPI version JSON
download
home_pagehttps://github.com/PlanesLab/gMCSpy
SummarygMCSpy is a python package for the calculation of Genetic Minimal Cut sets (GMCS). In simple terms the idea is to take a metabolic model and calculate the genetic vulnerabilities that will render the biomass production impossible. This is done through a Mixed-Integer Linear problem (MILP) formultion and the use of a linear solver.
upload_time2024-03-18 12:20:12
maintainer
docs_urlNone
authorCarlos Javier Rodriguez
requires_python
licenseMIT
keywords gmcs genetic minimal cut sets gurobi cplex
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            
            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/PlanesLab/gMCSpy",
    "name": "gMCSpy",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "gMCS,Genetic Minimal Cut Sets,Gurobi,CPLEX",
    "author": "Carlos Javier Rodriguez",
    "author_email": "cjrodriguezf@unav.es",
    "download_url": "https://files.pythonhosted.org/packages/b4/e2/b8dbb06f8d3b20a2768d4d58d95019be975ef18914403d5c2967fd7775d8/gMCSpy-1.0.1.tar.gz",
    "platform": null,
    "description": "",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "gMCSpy is a python package for the calculation of Genetic Minimal Cut sets (GMCS). In simple terms the idea is to take a metabolic model and calculate the genetic vulnerabilities that will render the biomass production impossible. This is done through a Mixed-Integer Linear problem (MILP) formultion and the use of a linear solver.",
    "version": "1.0.1",
    "project_urls": {
        "Download": "https://github.com/PlanesLab/gMCSpy/archive/refs/tags/v.1.0.1.tar.gz",
        "Homepage": "https://github.com/PlanesLab/gMCSpy"
    },
    "split_keywords": [
        "gmcs",
        "genetic minimal cut sets",
        "gurobi",
        "cplex"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "b4e2b8dbb06f8d3b20a2768d4d58d95019be975ef18914403d5c2967fd7775d8",
                "md5": "03f2a095e5b3b95ae1996de77a963dcc",
                "sha256": "72c9e434d6fcd49808a4560774033cb62f6fb7ddd0a73cdfa5cf63d532923f02"
            },
            "downloads": -1,
            "filename": "gMCSpy-1.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "03f2a095e5b3b95ae1996de77a963dcc",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 35485,
            "upload_time": "2024-03-18T12:20:12",
            "upload_time_iso_8601": "2024-03-18T12:20:12.801748Z",
            "url": "https://files.pythonhosted.org/packages/b4/e2/b8dbb06f8d3b20a2768d4d58d95019be975ef18914403d5c2967fd7775d8/gMCSpy-1.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-03-18 12:20:12",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "PlanesLab",
    "github_project": "gMCSpy",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "lcname": "gmcspy"
}
        
Elapsed time: 0.22054s