GECKO#
MATLAB & Python
Reconstruction, simulation and analysis of enzyme-constrained metabolic models (ecModels): a MATLAB toolbox built on RAVEN, and geckopy, a Python port built on cobrapy.
Install#
pip install --pre geckopy
--pre is required while geckopy and raven-toolbox are pre-releases on
PyPI.
pip install \
git+https://github.com/CompMetEng/raven-toolbox.git@develop \
git+https://github.com/CompMetEng/geckopy.git@develop
Tracks the develop branch of both packages, ahead of the latest PyPI
release.
Home → Add-Ons → Get Add-Ons → search “GECKO Toolbox”.
git clone --depth=1 https://github.com/CompMetEng/GECKO
Then run GECKOInstaller.install in MATLAB.
Key features#
Convert a conventional GEM into an ecModel by bounding reaction rates with enzyme kcat and abundance.
Constrain individual enzyme usage with absolute or relative proteomics measurements.
A smaller, faster-simulating ecModel variant for when full proteome coverage isn’t needed.
Quick start#
from geckopy import load_ec_model
# load a previously built ecModel
model = load_ec_model("ecYeastGEM.yml")
# set growth as the objective
model.objective = "r_2111"
# run FBA -- simulation comes from cobrapy, unchanged
sol = model.optimize()
print(f"Growth rate: {sol.objective_value:.4f} h⁻¹")
% load a previously built ecModel
model = loadEcModel('ecYeastGEM.yml');
% set growth as the objective
model = setParam(model, 'obj', 'r_2111', 1);
% run FBA
sol = solveLP(model);
fprintf('Growth rate: %.4f h-1\n', sol.f);
Documentation#
Task-focused pages covering the full ecModel pipeline, MATLAB and Python side by side.
Complete function reference for both GECKO (MATLAB) and geckopy (Python).
Set up GECKO in MATLAB or geckopy in Python, plus the Gurobi/SoPlex solver and Docker for DLKcat.
Which to use for what, what only one of them has, and where the same function gives a different answer.
Citing GECKO#
If you use GECKO in your research, please cite:
Chen, Y., Gustafsson, J., Tafur Rangel, A., Anton, M., Domenzain, I., Kittikunapong, C., Li, F., Yuan, L., Nielsen, J. & Kerkhoven, E. J. Reconstruction, simulation and analysis of enzyme-constrained metabolic models using GECKO Toolbox 3.0. Nature Protocols 19, 629-667 (2024). https://doi.org/10.1038/s41596-023-00931-7
See Citations for the full list, including key papers that have used this protocol.
Source code#
GECKO is publicly available under the MIT license at CompMetEng/GECKO, archived at https://doi.org/10.5281/zenodo.7699818. geckopy, the Python port, is at CompMetEng/geckopy.
Getting help#
Report a bug or request a feature against whichever implementation it concerns; ask a usage question in either repository’s Discussions.
Issues |
Discussions |
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GECKO (MATLAB) |
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geckopy (Python) |