STARGATE-X: a Python package for statistical analysis on the REACTOME network

Area of Science:

• Bioinformatics
• Systems Biology
• Molecular Biology

Background:

• Biological knowledge is often represented by molecular pathways.
• Pathways are crucial for understanding gene functions and developing bioinformatics tools.
• Biochemical networks, linking reactions and compounds, are key to pathway analysis.

Purpose of the Study:

• Introduce StARGate-X, a tool for automated analysis of Reactome's biochemical reaction network and biological hierarchy.
• Demonstrate the tool's effectiveness through centrality measures (in- and out-degree) of the Reactome network.
• Provide a freely available, easy-to-use API for analyzing large biochemical networks.

Main Methods:

• Developed StARGate-X (Statistical Analysis of the Reactome multi-Graph Through nEtworkX) for automated network analysis.
• Utilized network analysis techniques, focusing on connectivity properties and centrality measures.
• Analyzed subgraphs induced by cell compartments and the graph of strongly connected components.

Main Results:

• StARGate-X successfully performed automated analysis of Reactome's network connectivity and hierarchy.
• Centrality measures (in- and out-degree) were effectively applied to understand network properties.
• The analysis provided insights into the structure of Reactome pathways within different cellular compartments.

Conclusions:

• StARGate-X is the first freely available tool for automated analysis of the Reactome biochemical network using APIs.
• The tool enhances mechanistic insights and gene list interpretation in systems biology.
• Automated analysis of biochemical networks facilitates deeper understanding of molecular mechanisms.