PEtab-GUI

PEtab-GUI provides a graphical user interface to inspect and edit parameter estimation problems encoded in the PEtab format.

Installation

From PyPI

To install PEtab-GUI from PyPI, run:

pip install petab_gui

or, to install PEtab-GUI in a dedicated virtual environment using pipx (to be installed separately), run:

pipx install petab_gui

From GitHub

To install the latest development version from GitHub, run:

pip install git+https://github.com/PEtab-dev/PEtab-GUI/

From a local copy

1. Clone the repository:

   git clone https://github.com/PEtab-dev/PEtab-GUI.git
   

2. Install the package from the root of the working tree:

   pip install .
   

Usage

After installation, launch PEtab-GUI from the command line using the petab_gui command.

Optionally, you can provide the path to an existing PEtab YAML file as an argument.

After loading a PEtab problem, PEtab-GUI will look something like this:

Examples

PEtab-GUI comes with two examples of its own, which can be immediately loaded from the File menu.

A more extensive set of real-world PEtab problems is available in the PEtab benchmark collection.

Download and unpack the archive, then open one of the YAML files inside Benchmark-Models/*/ using PEtab-GUI. Benchmark-Models/Boehm_JProteomeRes2014/Boehm_JProteomeRes2014.yaml should serve as a good starting point.

Features

The PEtab-GUI provides a Python-based graphical user interface that simplifies the creation, editing, and validation of PEtab parameter estimation problems.

• Unified Environment
  • Integrates all PEtab components (SBML models, conditions, observables, measurements, parameters, and visualization files).
  • Supports drag-and-drop import of YAML or individual component files.
  • Automatically resolves mismatches and converts matrix-format experimental data into valid PEtab format.
• Interactive and Intuitive Editing
  • Dockable, resizable, and movable table widgets for each PEtab file.
  • Context-aware editing with combo-boxes, drop-downs, and multi-cell editing.
  • Automatic generation of missing observables/conditions with customizable defaults.
  • Real-time validation and plausibility checks with PEtab linting tools.
  • SBML view in both XML and human-readable Antimony syntax.
• Visualization and Simulation
  • Interactive plots linking measurement data with model simulations.
  • Bidirectional highlighting between plots and tables.
  • Built-in simulation via BasiCO with one-click parameter testing.
  • Intelligent defaults for visualization with optional user customization.
  • Ability to disable plotting for large models to maintain responsiveness.
• Archiving and Export
  • Export individual tables, the SBML model, or complete PEtab problems.
  • Save as directory structures or COMBINE archives for reproducibility