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StonPy: a tool to parse and query collections of SBGN maps in a graph database
Adrien Rougny1,2, Irina Balaur3, Augustin Luna4,5
1Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan.
Bioinformatics (Oxford, England)
|March 10, 2023
Summary
StonPy provides a novel solution for storing and querying Systems Biology Graphical Notation (SBGN) maps using a graph database. This tool facilitates efficient semantic analysis of molecular maps.
Area of Science:
- Systems Biology
- Bioinformatics
- Computational Biology
Background:
- Systems Biology Graphical Notation (SBGN) is the standard for molecular map representation.
- Analyzing large collections of SBGN maps requires efficient data access and querying.
- Existing methods may lack comprehensive support for SBGN's diverse languages and semantic analysis.
Purpose of the Study:
- To introduce StonPy, a new tool for storing and querying SBGN maps.
- To enable semantic and graph-based analysis of large SBGN map datasets.
- To provide a flexible library and command-line interface for SBGN map manipulation.
Main Methods:
- Utilizing a Neo4j graph database for storing SBGN map data.
- Developing a data model supporting all three SBGN languages.
- Implementing a completion module for automatic SBGN map construction from query results.
- Building StonPy as an integrable Python library with a command-line interface.
Main Results:
- StonPy enables efficient storage and querying of SBGN maps.
- The tool supports all SBGN languages within a unified data model.
- Automatic map completion from query results enhances usability.
- StonPy is readily integrable into existing bioinformatics workflows.
Conclusions:
- StonPy offers a robust solution for managing and analyzing SBGN maps.
- The tool facilitates advanced semantic and graph-based analyses of biological pathway data.
- StonPy's design promotes accessibility and integration within the research community.
