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mewpy

Metabolic Engineering Workbench

https://github.com/biosystemsum/mewpy

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ○
    Academic publication links
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    Committers with academic emails
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.7%) to scientific vocabulary

Keywords

kinetic-modeling microbial-communities modeling omics-data-integration optimization python simulation strain
Last synced: 6 months ago · JSON representation

Repository

Metabolic Engineering Workbench

Basic Info
  • Host: GitHub
  • Owner: BioSystemsUM
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Homepage: https://mewpy.readthedocs.io
  • Size: 28.6 MB
Statistics
  • Stars: 34
  • Watchers: 10
  • Forks: 11
  • Open Issues: 1
  • Releases: 0
Topics
kinetic-modeling microbial-communities modeling omics-data-integration optimization python simulation strain
Created almost 6 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.md

License: GPL v3 PyPI version Documentation Status Build Status

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:

  • Simulation: allows to simulate steady-state metabolic models, considering different formulations (e.g., GECKO, ETFL) and kinetic models;
  • Omics data integration (eFlux, GIMME, iMAT);
  • Optimization: performs Evolutionary Computation based strain design optimization by knocking out (KO) or over/under expressing (OU) reactions, genes or enzymes.

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/BioSystemsUM/mewpy.git -b master

  1. run python setup.py install

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

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

MEWpy is currently mantained by Vítor Pereira.

Released under an Apache License.

Owner

  • Name: BioSystems@CEB - Centre of Biological Engineering
  • Login: BioSystemsUM
  • Kind: organization
  • Location: Braga, Portugal

GitHub Events

Total
  • Issues event: 3
  • Watch event: 5
  • Issue comment event: 1
  • Fork event: 2
Last Year
  • Issues event: 3
  • Watch event: 5
  • Issue comment event: 1
  • Fork event: 2

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 576
  • Total Committers: 3
  • Avg Commits per committer: 192.0
  • Development Distribution Score (DDS): 0.51
Past Year
  • Commits: 140
  • Committers: 1
  • Avg Commits per committer: 140.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Vítor Pereira v****a@g****m 282
Vítor Pereira v****a@a****t 202
cruz-f f****4@g****m 92
Committer Domains (Top 20 + Academic)
algoritmi.uminho.pt: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 13
  • Total pull requests: 32
  • Average time to close issues: 15 days
  • Average time to close pull requests: about 1 hour
  • Total issue authors: 8
  • Total pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.09
  • Merged pull requests: 31
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 minute
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jinb88187 (3)
  • Laminsecin (2)
  • cdanielmachado (2)
  • maozhitao (2)
  • revas (1)
  • SiYeon-Ju (1)
  • thuwilliamwyx (1)
  • V0idLord (1)
  • pg42866 (1)
  • FelipeMelis (1)
  • mkulyashov (1)
  • Rohak72 (1)
Pull Request Authors
  • vmspereira (31)
  • cruz-f (2)
  • thuwilliamwyx (1)
Top Labels
Issue Labels
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Dependencies

docs/requirements.txt pypi
  • nbsphinx *
requirements.txt pypi
  • cobra *
  • inspyred *
  • jmetalpy *
  • joblib *
  • matplotlib *
  • networkx *
  • numpy *
  • reframed *
  • tqdm *
.github/workflows/main.yaml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
pyproject.toml pypi
setup.py pypi