User Guide

Description

The moiety_modeling package provides a simple Python interface for moiety model representation, model optimization and model selection. Both moiety models and isotopologue datasets are stored in`JSON` files, which can be used for further model optimization, selection, analysis and visualization.

Installation

moiety_modeling runs under Python 3.6+ and is available through python3-pip. Install via pip or clone the git repo and install the following dependencies and you are ready to go!

Install on Linux

Pip installation (method 1)

python3 -m pip install moiety-modeling

GitHub Package installation (method 2)

Make sure you have git installed:

git clone https://github.com/MoseleyBioinformaticsLab/moiety_modeling.git

Dependecies

moiety_modeling requires the following Python libraries:

• docopt for creating the command-line interface.
• jsonpickle for saving Python objects in a JSON serializable form and outputting to a file.
• numpy and matplotlib for visualization of optimized results.
• scipy for application of optimization methods.
• SAGA-optimize for parameters optimization.

Basic usage

The moiety_modeling package can be used in several ways:

• As a library for accessing and manipulating moiety models and isotopologue datasets stored in the JSON files.

• As a command-line tool:

  • Optimize the moiety model parameters.
  • Analyze the optimization results of moiety model, and select the optimal model.
  • Visuslize the optimized results.

Note

Read The moiety_modeling Tutorial to learn more and see code examples on using the moiety_modeling as a library and as a command-line tool.