Skip to main content

Python package for building and analyzing models using ModelSEED

Project description

https://raw.githubusercontent.com/modelseed/modelseedpy/main/examples/ms-logo-horizontal.png?sanitize=true

Metabolic modeling with the ModelSEED Database

PyPI version Documentation Status Downloads License

Metabolic modeling is an pivotal method for computational research in synthetic biology and precision medicine. The metabolic models, such as the constrint-based flux balance analysis (FBA) algorithm, are improved with comprehensive datasets that capture more metabolic chemistry in the model and improve the accuracy of simulation predictions. We therefore developed ModelSEEDpy as a comprehensive suite of packages that bootstrap metabolic modeling with the ModelSEED Database (Seaver et al., 2021 ). These packages parse and manipulate (e.g. gapfill missing reactions or calculated chemical properties of metabolites), constrain (with kinetic, thermodynamics, and nutrient uptake), and simulate cobrakbase models (both individual models and communities). This is achieved by standardizing COBRA models through the cobrakbase module into a form that is amenable with the KBase/ModelSEED ecosystem. These functionalities are exemplified in Python Notebooks . Please submit errors, inquiries, or suggestions as GitHub issues where they can be addressed by our developers.

Installation

ModelSEEDpy will soon be installable via the PyPI channel:

pip install modelseedpy

but, until then, the repository must cloned:

git clone https://github.com/ModelSEED/ModelSEEDpy.git

and then locally installed with pip:

cd path/to/modelseedpy
pip install .

The associated ModelSEED Database, which is required for a few packages, is simply downloaded by cloning the GitHub repository:

git clone https://github.com/ModelSEED/ModelSEEDDatabase.git

and the path to this repository is passed as an argument to the corresponding packages.

Windows users must separately install the pyeda module: 1) download the appropriate wheel for your Python version from this website ; and 2) install the wheel through the following commands in a command prompt/powershell console:

cd path/to/pyeda/wheel
pip install pyeda_wheel_name.whl

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

ModelSEEDpy-freiburgermsu-0.3.1.0.tar.gz (2.9 MB view details)

Uploaded Source

File details

Details for the file ModelSEEDpy-freiburgermsu-0.3.1.0.tar.gz.

File metadata

File hashes

Hashes for ModelSEEDpy-freiburgermsu-0.3.1.0.tar.gz
Algorithm Hash digest
SHA256 b74ad8adf130f20a478297097465a61e5b3c3cec9b3fd593f3588941aa371226
MD5 acc238b9ff3c238fe6f3f1e575e144c4
BLAKE2b-256 e6d3f21da8c199ddac8aff9b5692dbfbc0c5fdc5a9d9d3746f00cf8bab30425a

See more details on using hashes here.

Supported by

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