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Python package for pathway-centric modification and extension of genome-scale metabolic networks

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CobraMod: A pathway-centric curation tool for constraint-based metabolic models


CobraMod is a Python 3 open-source package for pathway-centric curation of genome-scale metabolic models (GEMs). It builds upon the COBRApy toolbox and offers a comprehensible set of functions for semi-automated network extension, curation and visualization. CobraMod supports all databases from the BioCyc collection, the KEGG database, and the BiGG Models repository and can directly interact with Escher for pathway and flux visualization.

This package converts pathway information into native COBRApy objects and quality-checks them while adding them to the model. This includes testing for:

  • duplicate elements
  • correct chemical formula
  • mass balance of reactions
  • reaction reversibility
  • capability to carry non-zero fluxes
  • adding available gene information
  • MEMOTE compliance
  • available cross-references

CobraMod offers user-friendly tracking of the curation process with summary output and log files and customized pathway and flux visualization with Escher.


CobraMod can easily be installed using pip :

pip install cobramod


This package offers multiple functions for modifying and extending GEMs:

  • Retrieve metabolic pathway information from a database cobramod.get_data
  • Transform stored data into COBRApy objects cobramod.create_object
  • Add metabolites from multiple sources cobramod.add_metabolites
  • Add reactions from multiple sources cobramod.add_reactions
  • Test reaction capability to carry a non-zero flux cobramod.test_non_zero_flux
  • Add pathway to a model cobramod.add_pathway
  • Automatic cross-references cobramod.add_crossreferences
  • Testing for MEMOTE compliance

Check the documentation for more information.

Citing CobraMod

To cite CobraMod, please use the following paper:

CobraMod: a pathway-centric curation tool for constraint-based metabolic models

    author = {Camborda, Stefano and Weder, Jan-Niklas and Töpfer, Nadine},
    title = "{CobraMod: a pathway-centric curation tool for constraint-based metabolic models}",
    journal = {Bioinformatics},
    volume = {38},
    number = {9},
    pages = {2654-2656},
    year = {2022},
    month = {02},
    abstract = "{COnstraint-Based Reconstruction and Analysis of genome-scale metabolic models has become a widely used tool to understand metabolic network behavior at a large scale. However, existing reconstruction tools lack functionalities to address modellers' common objective to study metabolic networks on the pathway level. Thus, we developed CobraMod—a Python package for pathway-centric modification and extension of genome-scale metabolic networks. CobraMod can integrate data from various metabolic pathway databases as well as user-curated information. Our tool tests newly added metabolites, reactions and pathways against multiple curation criteria, suggests manual curation steps and provides the user with records of changes to ensure high quality metabolic reconstructions. CobraMod uses the visualization tool Escher for pathway representation and offers simple customization options for comparison of pathways and flux distributions. Our package enables coherent and reproducible workflows as it can be seamlessly integrated with COBRApy and Escher.The source code can be found at and can be installed with pip. The documentation including tutorials is available at}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btac119},
    url = {},
    eprint = {},


CobraMod is licensed under the GPL-3 License. Read the LICENSE for more information.


You can contribute to CobraMod by cloning the repository and installing it in developer mode using pip :

pip install -e .

A conda environment file is supplied (environment.yml). This file contains all the dependencies to ensure reproducibility of the package. We encourage pull requests. CobraMod uses unit testing and new tests are welcome.

To report bugs and suggestions, please create an issue using the corresponding tags at

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