mxlbricks 0.9.0

A package to build metabolic models

MxlBricks

MxlBricks is a Python package to build mechanistic models composed of pre-defined reactions (bricks). This facilitates re-use and interoperability between different models by sharing common parts.

Installation

You can install mxlpy using pip: pip install mxlbricks.

If you want access to the sundials solver suite via the assimulo package, we recommend setting up a virtual environment via pixi or mamba / conda using the conda-forge channel.

pixi init
pixi add python assimulo
pixi add --pypi mxlbricks

Development setup

Install pixi as described in the docs.

Run

pixi install

Models

Name	Description
Ebenhöh 2011	PSII & two-state quencher & ATP synthase
Ebenhöh 2014	PETC & state transitions & ATP synthase from Ebenhoeh 2011
Matuszyńska 2016 NPQ	2011 + PSII & four-state quencher
Matuszyńska 2016 PhD	?
Matuszyńska 2019	Merges PETC (Ebenhöh 2014), NPQ (Matuszynska 2016) and CBB (Poolman 2000)
Saadat 2021	2019 + Mehler (Valero ?) & Thioredoxin & extendend PSI states & consumption
van Aalst 2023	Saadat 2021 & Yokota 1985 & Witzel 2010

References

Name	Description
Poolman 2000	CBB cycle, based on Pettersson & Ryde-Pettersson 1988
Yokota 1985	Photorespiration
Valero ?

Tool family 🏠

MxlBricks is part of a larger family of tools that are designed with a similar set of abstractions. Check them out!

• MxlPy is a Python package for mechanistic learning (Mxl)
• MxlModels supplies flat, single-file versions of MxlBricks models for easy inspection
• MxlWeb brings simulation of mechanistic models to the browser!
• pysbml simplifies SBML models for import/export with MxlPy
• Parameteriser looks up kinetic parameters from BRENDA and other databases