README.rst

Maud

Maud is a work-in-progress application that fits Bayesian statistical models of metabolic networks using Python and Stan.

Maud aims to take into account allosteric effects, ensure that the laws of thermodynamics are obeyed and to synthesise information from both steady state experiments and the existing literature.

Install

First create a fresh Python 3.7 virtual environment and then activate it:

sudo pip3.7 install virtualenv     # if virtualenv isn't installed already
python3.7 -m virtualenv maud_venv  # choose any name you like!
source maud_venv/bin/activate

To install the latest Maud and its python dependencies to your new virtual environment from the latest master branch, run this command:

pip install https://github.com/biosustain/Maud/archive/master.zip

Cmdstanpy depends on cmdstan, which needs to be installed too. Fortunately, cmdstanpy comes with a command line script that installs cmdstan, so this step is pretty simple:

install_cmdstan

Usage

To run the simple linear model, use the following command:

maud sample

This will use the data file at data/in/linar.toml to create a Stan program called inference_model_linear.stan in your working directory, compile it into a C++ Stan model, draw samples from the resulting posterior and store them in csv files starting with model_output_linear.

The sample command can be configured in a few ways - to check out all the options try running

maud sample --help

Copyright

• Copyright (c) 2019, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark.
• Free software distributed under the GNU General Public License 3.0