MEWpy is an integrated Metabolic Engineering Workbench, under development, for strain design optimization. Developed in Python, MEWpy offers methods to explore different classes of constraint-based models (CBM).
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Simulation: allows to simulate different metabolic models considering different phenotype.
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Optimization: performs Evolutionary Computation based strain design optimization by knocking out (KO) or over/under expressing (OU) reactions, genes or enzymes.
Metabolic Constraints
Method Strategy Reactions KO / OU Genes (GPRs) KO / OU Enzymatic Constraints
Method Strategy GECKO KO / OU sMOMENT KO / OU Regulatory Constraints
Method Strategy OptRAM KO / OU OptORF KO -
MEWPy currently supports REFRAMED and COBRApy simulation environments.
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The optimization engine relies on either inspyred or jMetalPy packages, which are used for creating biologically-inspired computational intelligence algorithms in Python.
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Next releases will enable simulation and optimization strategies for Expression and Thermodynamics Flux (ETFL) and Metabolism and Macromolecular Expression (ME) models.
Examples are provided as in the as jupiter notebooks and as python scripts.
The package documentation is avaliable at mewpy.readthedocs.io.
Installing from Pypi package repository:
pip install mewpy
Installing from github:
- clone the repository
git clone https://github.com/BioSystemsUM/mewpy.git
- run
python setup.py install
MEWPy requires a compatible solver for linear programming problems, with installed Python dependencies installed, from the following list:
Developed at Centre of Biological Engineering, University of Minho (2019-2020)
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 814408.
Released under an Apache License.