mewpy 0.1.36

MEWpy - Metabolic Engineering in Python

MEWpy

MEWpy is an integrated Metabolic Engineering Workbench for strain design optimization. It offers methods to explore different classes of constraint-based models (CBM) for:

• Simulating single organisms: allows to simulate steady-state metabolic models, considering different formulations (e.g., GECKO, ETFL) and kinetic models;
• Evolutionary Computation based strain design optimization by knocking out (KO) or over/under expressing (OU) reactions, genes or enzymes.
• Omics data integration (eFlux, GIMME, iMAT);
• Regulatory Networks integration;
• Microbial Community Modeling: Community simulation and optimization, SMETANA, SteadyCOM;

MEWPy currently supports REFRAMED and COBRApy simulation environments. The optimization engine relies on either inspyred or jMetalPy packages.

Examples

Examples are provided as jupyter notebooks and as python scripts.

Documentation

The package documentation is available at mewpy.readthedocs.io.

Instalation

Installing from Pypi package repository:

pip install mewpy

Installing from github:

1. clone the repository

git clone https://github.com/vmspereira/MEWpy.git -b master

2. run python setup.py install

MEWPy requires a compatible linear programming solver, with installed Python dependencies, from the following list:

• CPLEX
• GUROBI
• GLPK

Cite

If you use MEWpy in your research, please cite:

Vítor Pereira, Fernando Cruz, Miguel Rocha, MEWpy: a computational strain optimization workbench in Python, Bioinformatics, 2021; https://doi.org/10.1093/bioinformatics/btab013

Credits and License

Developed by Vítor Pereira and Centre of Biological Engineering, University of Minho. MEWpy received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 814408 (2019-2023).

MEWpy is currently mantained by Vítor Pereira.

Released under an Apache License.