Maud is a tool for fitting Bayesian statistical models of metabolic networks.
Maud's distinguishing features include:
- Scientifically accurate representation of phenomena including enzyme kinetics, allosteric regulation, competitive inhibition, phosphorylation, knockouts and transported charges.
- Guaranteed consistency with thermodynamic and steady state constraints.
- A statistical model allowing inference consistent with both information from experiments and pre-experimental background information.
- Prediction of steady state concentrations and fluxes given unseen boundary conditions.
More practically speaking, Maud is a command line application that uses Stan to specify and fit a statistical model and Python to interface between Stan and humans.
.. toctree:: :maxdepth: 1 :caption: How to use Maud: usage/installation usage/inputting usage/post_installation_usage
.. toctree:: :maxdepth: 1 :caption: Theoretical background: theory/enzyme_kinetics theory/kinetic_model theory/statistics theory/thermodynamics theory/drains theory/transported_charges theory/papers
.. toctree:: :maxdepth: 1 :caption: How Maud works: how_maud_works/data_model how_maud_works/computation