Welcome to Maud’s documentation!

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.

How to use Maud:

• Installation
• Specifying input data
• Running Maud
• Contributing to Maud

Theoretical background:

• Enzyme kinetics
• Kinetic Models
• Statistical Model
• Thermodynamics
• Drain Reactions
• Transport of charged molecules
• Relevant Reading

How Maud works:

• Maud’s data model
• Computation

Indices and tables

• Index

• Module Index

• Search Page