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momapy: a Python library to work with molecular maps.

Adrien Rougny¹, Marek Ostaszewski¹, Venkata Sagatopam¹

¹Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.

Bioinformatics (Oxford, England)

|June 3, 2026

Summary

This summary is machine-generated.

A new Python library, momapy, enables programmatic analysis and comparison of molecular maps. This tool facilitates the extraction of biological concepts from graphical representations, enhancing data analysis and modeling capabilities.

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Area of Science:

Systems Biology
Bioinformatics
Computational Biology

Background:

Molecular maps visualize biological system mechanisms, aiding knowledge curation and data analysis.
Existing software supports molecular maps but lacks advanced programmatic analysis and comparison tools.
Programmatic access is needed for extracting biological concepts and comparing map representations.

Purpose of the Study:

To introduce momapy, a Python library for programmatic interaction with molecular maps.
To enable separation of map data models from their graphical representations.
To facilitate map manipulation and comparison through a unified interface.

Main Methods:

Developed momapy as a generic Python library.
Implemented support for Systems Biology Graphical Notation (SBGN) and CellDesigner formats.
Designed momapy for extensibility to new formats and functionalities.

Main Results:

momapy allows programmatic extraction and separation of molecular map data models.
Users can perform base operations like manipulation and comparison on map data.
The library supports established standards like SBGN and CellDesigner.

Conclusions:

momapy provides essential tools for advanced programmatic analysis of molecular maps.
This library enhances the utility of molecular maps for data analysis and modeling.
momapy is freely available with comprehensive documentation for researchers.