Skip to main content

Multi-objective GEMs metabolic interaction inference

Project description

MIMEco is python package that explores communities metabolic interactions using multi-objective linear programming on GEnome-scale Metabolic models (GEMs). This tool automates the inference of interaction type, interaction score and exchanged metabolites between two models in a given condition.

The concept of the methodology is described in Lambert, A., Budinich, M., Mahé, M., Chaffron, S., & Eveillard, D. (2024). Community metabolic modeling of host-microbiota interactions through multi-objective optimization. Iscience, 27(6). (http://doi.org/10.1016/j.isci.2024.110092)

Note : A technical note dedicated to this package will be published

MIMEco logo

Documentation

For detailed documentation, please go to readthedocs : mimeco

Dependencies

GLPK: MIMEco depends on benpy, which needs glpk to function. Its installation is clearly described in benpy’s pyPI page

Efficient solver To use MIMEco, you will need to download a solver, preferably CPLEX or gurobi. Both are free for academics, but require to get a license to be used at full capacity. A tutorial on how to make gurobi work with mimeco is written in the documentation

Installation

MIMEco is available on pyPI. You can install it with pip install mimeco

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimeco-0.1.20.tar.gz (993.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mimeco-0.1.20-py3-none-any.whl (429.2 kB view details)

Uploaded Python 3

File details

Details for the file mimeco-0.1.20.tar.gz.

File metadata

  • Download URL: mimeco-0.1.20.tar.gz
  • Upload date:
  • Size: 993.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for mimeco-0.1.20.tar.gz
Algorithm Hash digest
SHA256 a39d18f6a7c5d3d175d8bde7497fe8ce19b14d03d3bffd784dac14884a3ad6a4
MD5 83b352f0f36d336a3d210ba9d451e09d
BLAKE2b-256 1346bd62e353540ee97e1b91a2c305ad4f315c8a7bedf6171377c5431c1adbcb

See more details on using hashes here.

File details

Details for the file mimeco-0.1.20-py3-none-any.whl.

File metadata

  • Download URL: mimeco-0.1.20-py3-none-any.whl
  • Upload date:
  • Size: 429.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for mimeco-0.1.20-py3-none-any.whl
Algorithm Hash digest
SHA256 e270e88dec4d78ce8d454a53818632075ab533b3918115b8605aa42cd92807dc
MD5 b73c2a7711f11c4a4ec1e3e8cf5c6232
BLAKE2b-256 0452745b7631571dcd00a193b51dfb7492513e68a577a7c982a32f20d6dcd160

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page