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        "author": "Hyejin Kang",
        "author_email": "gpwls23@snu.ac.kr",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Topic :: Utilities"
        ],
        "description": "========\nOverview\n========\n\n\n\nA new pipeline, mirTime, that predicts microRNA targets by integrating sequence features and time-series expression\nprofiles in a specific experimental condition.\n\n* Free software: MIT license\n\nInstallation\n============\n\n::\n\n    pip install mirtime\n\nDocumentation\n=============\n\n\nhttps://python-mirtime.readthedocs.io/\n\n\nDevelopment\n===========\n\nTo run the all tests run::\n\n    tox\n\nNote, to combine the coverage data from all the tox environments run:\n\n.. list-table::\n    :widths: 10 90\n    :stub-columns: 1\n\n    - - Windows\n      - ::\n\n            set PYTEST_ADDOPTS=--cov-append\n            tox\n\n    - - Other\n      - ::\n\n            PYTEST_ADDOPTS=--cov-append tox\n\n\nChangelog\n=========\n\n0.1.0 (2019-01-14)\n------------------\n\n* First release on PyPI.\n\n\n",
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        "keywords": "",
        "license": "MIT license",
        "maintainer": "",
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        "name": "mirtime",
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        "summary": "A new pipeline, mirTime, that predicts microRNA targets by integrating sequence features and time-series expression profiles in a specific experimental condition.",
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