StonPy

StonPy stores, queries, and manipulates Systems Biology Graphical Notation (SBGN) maps in a Neo4j graph database to enable semantic and graph-based analysis of molecular interactions and pathways.

Key Features:

• Neo4j integration: Stores SBGN maps in a Neo4j graph database and supports complex graph queries for analysis.
• Comprehensive SBGN data model: Represents all three SBGN languages—Process Description (PD), Entity Relationship (ER), and Activity Flow (AF)—within the database model.
• Automatic map completion: Includes a completion module that constructs valid SBGN maps from query results.
• Semantic and graph-based analysis: Enables semantic exploration and graph-structure analyses of molecular interactions and pathways.
• Management of large map collections: Supports storage and manipulation of extensive collections of molecular maps.

Scientific Applications:

• Semantic analysis: Exploration of semantic content in SBGN maps to identify relationships and patterns among biological entities.
• Graph-based network analysis: Investigation of biological networks and pathway topology using Neo4j graph queries.
• Data integration and validation: Generation of valid SBGN maps from query results to ensure consistency and validate integrated data.
• Systems biology map management: Organization and querying of large SBGN map collections for systems biology research.

Methodology:

Stores SBGN maps in Neo4j, uses Neo4j complex queries for semantic and graph-based analyses, employs a data model representing PD, ER, and AF, and uses a completion module to construct valid SBGN maps from query results; implemented in Python 3.