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cameo-0.9.0b1


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توضیحات

cameo - computer aided metabolic engineering & optimization
ویژگی مقدار
سیستم عامل -
نام فایل cameo-0.9.0b1
نام cameo
نسخه کتابخانه 0.9.0b1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Nikolaus Sonnenschein, Joao Cardoso, Emre Özdemir, Kristian Jensen
ایمیل نویسنده niko.sonnenschein@gmail.com
آدرس صفحه اصلی http://cameo.bio
آدرس اینترنتی https://pypi.org/project/cameo/
مجوز Apache License Version 2.0
Cameo—Computer Aided Metabolic Engineering and Optimization ----------------------------------------------------------- .. summary-start |Join the chat at https://gitter.im/biosustain/cameo| |PyPI| |License| |Build Status| |Coverage Status| |DOI| |zenhub| |binder| What is cameo? ~~~~~~~~~~~~~~ **Cameo** is a high-level python library developed to aid the strain design process in metabolic engineering projects. The library provides a modular framework of simulation and strain design methods that targets developers that want to develop new design algorithms and custom analysis workflows. Furthermore, it exposes a high-level API to users that just want to compute promising strain designs. Curious? Head over to `try.cameo.bio <http://try.cameo.bio>`__ and give it a try. Please cite https://doi.org/10.1021/acssynbio.7b00423 if you've used cameo in a scientific publication. .. summary-end Installation ~~~~~~~~~~~~ .. installation-start Use pip to install cameo from `PyPI <https://pypi.python.org/pypi/cameo>`__. :: $ pip install cameo In case you downloaded or cloned the source code from `GitHub <https://github.com/biosustain/cameo>`__ or your own fork, you can run the following to install cameo for development. :: $ pip install -e <path-to-cameo-repo> # recommended You might need to run these commands with administrative privileges if you're not using a virtual environment (using ``sudo`` for example). Please check the `documentation <http://cameo.bio/installation.html>`__ for further details. .. installation-end Documentation and Examples ~~~~~~~~~~~~~~~~~~~~~~~~~~ Documentation is available on `cameo.bio <http://cameo.bio>`__. Numerous `Jupyter notebooks <http://nbviewer.ipython.org/github/biosustain/cameo-notebooks/tree/master/>`__ provide examples and tutorials and also form part of the documentation. They are also availabe in executable form on (`try.cameo.bio <http://try.cameo.bio>`__). Furthermore, course materials for a two day cell factory engineering course are available `here <https://biosustain.github.io/cell-factory-design-course/>`__. .. showcase-start High-level API (for users) ^^^^^^^^^^^^^^^^^^^^^^^^^^ Compute strain engineering strategies for a desired product in a number of host organisms using the high-level interface (runtime is on the order of hours). :: from cameo.api import design design(product='L-Serine') `Output <http://nbviewer.ipython.org/github/biosustain/cameo-notebooks/blob/master/08-high-level-API.ipynb>`__ The high-level API can also be called from the command line. :: $ cameo design vanillin For more information run :: $ cameo --help Low-level API (for developers) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Find gene knockout targets using evolutionary computation. :: from cameo import models from cameo.strain_design.heuristic import GeneKnockoutOptimization from cameo.strain_design.heuristic.objective_functions import biomass_product_coupled_yield model = models.bigg.e_coli_core obj = biomass_product_coupled_yield( model.reactions.Biomass_Ecoli_core_w_GAM, model.reactions.EX_succ_e, model.reactions.EX_glc_e) ko = GeneKnockoutOptimization(model=model, objective_function=obj) ko.run(max_evaluations=50000, n=1, mutation_rate=0.15, indel_rate=0.185) `Output <http://nbviewer.ipython.org/github/biosustain/cameo-notebooks/blob/master/05-predict-gene-knockout-strategies.ipynb>`__ Predict heterologous pathways for a desired chemical. :: from cameo.strain_design import pathway_prediction predictor = pathway_prediction.PathwayPredictor(model) pathways = predictor.run(product="vanillin") `Output <http://nbviewer.ipython.org/github/biosustain/cameo-notebooks/blob/master/07-predict-heterologous-pathways.ipynb>`__ .. showcase-end Contributions ~~~~~~~~~~~~~ ... are very welcome! Please read the `guideline <CONTRIBUTING.rst>`__ for instructions how to contribute. .. url-marker .. |Join the chat at https://gitter.im/biosustain/cameo| image:: https://badges.gitter.im/biosustain/cameo.svg :target: https://gitter.im/biosustain/cameo?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge .. |PyPI| image:: https://img.shields.io/pypi/v/cameo.svg :target: https://pypi.python.org/pypi/cameo .. |License| image:: http://img.shields.io/badge/license-APACHE2-blue.svg :target: http://img.shields.io/badge/license-APACHE2-blue.svg .. |Build Status| image:: https://travis-ci.org/biosustain/cameo.svg?branch=master :target: https://travis-ci.org/biosustain/cameo .. |Coverage Status| image:: https://coveralls.io/repos/biosustain/cameo/badge.svg?branch=devel :target: https://coveralls.io/r/biosustain/cameo?branch=devel .. |DOI| image:: https://zenodo.org/badge/5031/biosustain/cameo.svg :target: https://zenodo.org/badge/latestdoi/5031/biosustain/cameo .. |zenhub| image:: https://img.shields.io/badge/Shipping_faster_with-ZenHub-5e60ba.svg?style=flat-square :target: https://zenhub.com .. |binder| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/biosustain/cameo-notebooks/binder?urlpath=lab/tree/index.ipynb


نیازمندی

مقدار نام
>=1.9.1 numpy
>=0.14.0 scipy
>=1.5.1 blessings
>=1.1.3 pandas
>=1.2 ordered-set
>=0.11.1 cobra
>=0.15.2 future
>=1.4.2 optlang
>=2.4 numexpr
>=2.10.0 requests
>=2.4 networkx
>=1.1.2 escher
>=0.4 IProgress
>=1.0 inspyred
>=1.2.0 lazy-object-proxy
>=2.1.1 palettable
==1.0.1 gnomic
>=2.4.5 openpyxl
>=6.7 click
<=0.12.1 bokeh
>=4.1.1 ipywidgets
- pytest-benchmark
>=3.6.0 lxml
>=5.13.0 python-libsbml
>=2.10.5 redis
>=4.12.0 plotly
>=1.0.0 jupyter
>=0.5 numpydoc
>=1.3.5 Sphinx
- pytest-cov
>=5.0.1 ipyparallel
- pytest
<=0.12.1 bokeh
>=1.3.5 Sphinx
>=0.5 numpydoc
>=1.0.0 jupyter
>=4.1.1 ipywidgets
>=2.10.5 redis
>=5.0.1 ipyparallel
>=4.12.0 plotly
>=5.13.0 python-libsbml
>=3.6.0 lxml
- pytest
- pytest-cov
- pytest-benchmark


نحوه نصب


نصب پکیج whl cameo-0.9.0b1:

    pip install cameo-0.9.0b1.whl


نصب پکیج tar.gz cameo-0.9.0b1:

    pip install cameo-0.9.0b1.tar.gz