Skip to main content

No project description provided

Project description

SCARCCpy - Simulation of Combined Antibiotics in Cross-feeding Communities

SCARCC is a python package developed by the Harcombe Lab designed to identify synergistic interactions between antibiotics within our two-species cross-feeding microbial community.

This package utilizes COBRA to analyze the perturbation effects caused by antibiotics in the genome-scale metabolic network using Flux Balance Analysis (FBA), and COMETS simulations to incorporate multispecies growth simulation using Dynamic Flux Balance Analysis (dFBA).

Documentation

The documentation is at readthedocs

Installation

Python version greater than Python 3.10 is required.

Use pip to install, use of virtual environment is encouraged.

For more detail setting up in MSI, see INSTALL.rst

pip install scarcc

License

The SCARCC source code is available under the MIT License.

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

scarcc-0.1.4.tar.gz (52.6 kB view details)

Uploaded Source

Built Distribution

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

scarcc-0.1.4-py3-none-any.whl (73.4 kB view details)

Uploaded Python 3

File details

Details for the file scarcc-0.1.4.tar.gz.

File metadata

  • Download URL: scarcc-0.1.4.tar.gz
  • Upload date:
  • Size: 52.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.1

File hashes

Hashes for scarcc-0.1.4.tar.gz
Algorithm Hash digest
SHA256 66b7031123efb6bafcf3fcf24f6c4005d50e5de0e80363836e5496a820ad644c
MD5 4a1937e72eeaaeede582fbc68d2a9f41
BLAKE2b-256 03c717a46f539e98f3fb821d40264f161f8a6fe8141cbe7e281ece19adcbf843

See more details on using hashes here.

File details

Details for the file scarcc-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: scarcc-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 73.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.1

File hashes

Hashes for scarcc-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 38c728b865a29fa6a3690e0154b921d5b0d1b877aeb31e72b6ba9b3b1c1600e7
MD5 01b3e9b7ce958bfdc37d70a4ce0a9f24
BLAKE2b-256 29430630b13a05b3c1acacca561eb6936abc078a8b74801dc6fc3d3deddfdbe9

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