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Methods for using the GECKO model with cobrapy

Project description

.. image:: GECKO.png

The **GECKO** toolbox is a Matlab/Python package for enhancing a
**G**\ enome-scale model to account for **E**\ nzyme **C**\ onstraints,
using **K**\ inetics and **O**\ mics. It is the companion software to
the publication:

Benjamin J. Sanchez, Cheng Zhang, Avlant Nilsson, Petri-Jaan Lahtvee,
Eduard J. Kerkhoven, Jens Nielsen (2017). *Improving the phenotype
predictions of a yeast genome-scale metabolic model by incorporating
enzymatic constraints.* `Molecular Systems Biology, 13(8):
935 <>`__

The software comes in two flavors, Python and Matlab scripts to fetch
online data and build the published ecYeast7 GECKO models, and a Python
package which can be used with
`cobrapy <>`__ to obtain a ecYeast7
model object, optionally adjusted for provided proteomics data.

Last update: 2017-12-08

This repository is administered by Benjamin J. Sanchez (`@BenjaSanchez <>`__), Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology.

Building a GECKO model

Required software - Python module

- `Python 2.7 <>`__
- `setuptools for python 2.7 <>`__
- SOAPpy: for this, open command prompt as admin, and then do:


cd C:\Python27\Scripts
easy_install-2.7 SOAPpy

Required software - Matlab module

- `MATLAB <>`__ (7.5 or higher) + Optimization
- The `COBRA toolbox for
MATLAB <>`__. Note that
`libSBML <>`__ and the `SBML
toolbox <>`__ should both be
installed. Both of them are free of charge for academic users.
Aditionally, you should add the cobra folder to your MATLAB search


See the supporting information of `Sanchez et al.
(2017) <>`__

Integrating proteomic data to the yeast model

If all you need is the ecYeast7 model to use together with cobrapy you
can use the ``geckopy`` Python package.

Required software

- Python 2.7, 3.4, 3.5 or 3.6
- cobrapy



pip install geckopy


.. code:: python

from geckopy import GeckoModel
import pandas
some_measurements = pandas.Series({'P00549': 0.1, 'P31373': 0.1, 'P31382': 0.1})
model = GeckoModel('multi-pool')


* Moritz Emanuel Beber (`@Midnighter <>`__), Danish Technical University, Lyngby Denmark
* Henning Redestig (`@hredestig <>`__), Danish Technical University, Lyngby Denmark
* `Benjamin J. Sanchez <>`__ (`@BenjaSanchez <>`__), Chalmers University of Technology, Gothenburg Sweden
* Cheng Zhang, Science for Life Laboratory, KTH - Royal Institute of Technology


0.0.1 (2017-09-07)

* First release on PyPI.

Project details

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