• scikit-bio™ is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics.

    Note: scikit-bio is no longer compatible with Python 2. scikit-bio is compatible with Python 3.6 and later.

    scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. To avoid these types of changes being a surprise to our users, our public APIs are decorated to make it clear to users when an API can be relied upon (stable) and when it may be subject to change (experimental). See the API stability docs for more details, including what we mean by stable and experimental in this context.

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    The recommended way to install scikit-bio is via the conda package manager available in Anaconda or miniconda.

    To install the latest release of scikit-bio:

    conda install -c http://conda.anaconda.org/biocore scikit-bio
    

    Alternatively, you can install scikit-bio using pip:

    pip install numpy
    pip install scikit-bio
    

    You can verify your installation by running the scikit-bio unit tests:

    python -m skbio.test
    

    For users of Debian, skbio is in the Debian software distribution and may be installed using:

    sudo apt-get install python3-skbio python-skbio-doc
    

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    To get help with scikit-bio, you should use the skbio tag on StackOverflow (SO). Before posting a question, check out SO's guide on how to 安卓手机安装tunsafe. The scikit-bio developers regularly monitor the skbio SO tag.

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    Some of the projects that we know of that are using scikit-bio are:

    • QIIME
    • Emperor
    • Gneiss
    • An Introduction to Applied Bioinformatics
    • tax2tree
    • Qiita
    • ghost-tree
    • Platypus-Conquistador

    If you're using scikit-bio in your own projects, feel free to issue a pull request to add them to this list.

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    If you're interested in getting involved in scikit-bio development, see CONTRIBUTING.md.

    See the list of scikit-bio's contributors.

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    scikit-bio is available under the new BSD license. See COPYING.txt for scikit-bio's license, and the tunsafe安装包 for the licenses of third-party software that is (either partially or entirely) distributed with scikit-bio.

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    scikit-bio began from code derived from PyCogent and QIIME, and the contributors and/or copyright holders have agreed to make the code they wrote for PyCogent and/or QIIME available under the BSD license. The contributors to PyCogent and/or QIIME modules that have been ported to scikit-bio are: Rob Knight (@rob-knight), Gavin Huttley (@gavin-huttley), Daniel McDonald (@wasade), Micah Hamady, Antonio Gonzalez (tunsafe安卓百度云), Sandra Smit, Greg Caporaso (@gregcaporaso), Jai Ram Rideout (@jairideout), Cathy Lozupone (@clozupone), Mike Robeson (@mikerobeson), Marcin Cieslik, Peter Maxwell, Jeremy Widmann, Zongzhi Liu, Michael Dwan, Logan Knecht (@loganknecht), Andrew Cochran, Jose Carlos Clemente (@cleme), Damien Coy, Levi McCracken, Andrew Butterfield, Will Van Treuren (@wdwvt1), Justin Kuczynski (@justin212k), Jose Antonio Navas Molina (@josenavas), Matthew Wakefield (@genomematt) and Jens Reeder (@jensreeder).

    苹果软件-免费软件站-海外加速器试用一小时-飞兔加速器ios下载

    scikit-bio's logo was created by Alina Prassas.

                                    飞鸟加速器,外网加速软件免费,暴喵加速器兑换码,爆猫加速器免费吗  instagram免费加速器,登lnstagram的加速器,ins免费加速神器,  黑洞vqn加速,黑洞vn加速器官网,黑洞加速下载器永久免费,  猎豹加速器,猎豹nvp加速器,猎豹vp加速器官网  Sakura破解版,Sakuramac下载,Sakura免费试用,Sakura跑路了  shadowrocket加速器破解版,shadowrocket加速器用不了了,shadowrocket加速器vp,shadowrocket加速器vqn  一元加速器pc版下载,一元加速器免费永久加速,一元加速器跑路了,一元加速器不能用了