geckopy

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G\ enome-scale model E\ nzyme C\ onstraints, using K\ inetics and O\ mics in py\ thon.

By combining kcats and proteomics measurement, geckopy allows for improving the modeling capabilities in genome-scale models.

..

Based on Sánchez et al., 2017_.

Citing geckopy: Carrasco et al., 2023_.

Check https://github.com/SysBioChalmers/GECKO for the matlab counterpart.

Overview

Load a model.

.. code-block:: python

import geckopy

model = geckopy.io.read_sbml_ec_model("tests/data/eciML1515.xml.gz") model.optimize()

Add copy number experimental data.

.. code-block:: python

import pandas as pd from geckopy.experiment import from_copy_number

raw_proteomics = pd.read_csv("tests/data/ecoli_proteomics_schmidt2016S5.tsv") exp_model = from_copy_number( model, index=raw_proteomics["uniprot"], cell_copies=raw_proteomics["copies_per_cell"], stdev=raw_proteomics["stdev"], vol=2.3, dens=1.105e-12, water=0.3, ) exp_model.optimize()

Add pool constraint.

.. code-block:: python

add some molecular weights to the proteins if the model does not have them

for prot in ec_model.proteins: prot.mw = 330 exp_model.constrain_pool( p_measured=12., sigma_saturation_factor=0.8, fn_mass_fraction_unmeasured_matched=0.2, ) print(exp_model.optimize()) print(exp_model.protein_pool_exchange)

Build the documentation

To build the documentation locally, run

.. code-block:: shell

cd docs pip install -r requirements.txt make ipy2rst # if there are notebooks for the docs at docs/notebooks make html

License

Copyright 2021 Ginkgo Bioworks.

Licensed under Apache License, Version 2.0, (LICENSE_ or http://www.apache.org/licenses/LICENSE-2.0).

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall 
be licensed as above, without any additional terms or conditions.

.. _Sánchez et al., 2017: https://dx.doi.org/10.15252/msb.20167411
.. _Carrasco et al., 2023: https://doi.org/10.1128/spectrum.01705-23
.. _LICENSE: ./LICENSE
.. _virtualenv: https://pypi.python.org/pypi/virtualenv