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GINv2.0: a comprehensive topological network integrating molecular interactions from multiple knowledge bases.

Xiao Chang¹, Shen Yan², Yizheng Zhang^3,4

¹Department of Dermatology and Venereal Disease, Xuan Wu Hospital, Beijing, 100053, China.

NPJ Systems Biology and Applications

|January 13, 2024

Summary

The Global Integrative Network (GIN) version 2.0 integrates human molecular interactions from ten databases, creating a unified resource for systems biology research. This enhanced network reveals coordinated regulation of glycolysis and autophagy, especially under glucose starvation.

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Area of Science:

Systems Biology
Bioinformatics
Molecular Networks

Background:

Biological knowledge bases are crucial for pathway analysis and data visualization in research.
Integrating diverse molecular interaction data from multiple sources into a unified network is challenging due to data complexity and varied formats.
Previous efforts, like the Global Integrative Network (GIN), were limited by relying on a single data source (KEGG).

Purpose of the Study:

To develop an improved version of the Global Integrative Network (GINv2.0) by integrating human molecular interaction data from ten distinct knowledge bases.
To standardize data structures and identifiers for comprehensive network integration.
To analyze biological processes and regulatory mechanisms using the unified network.

Main Methods:

Incorporated human molecular interaction data from ten knowledge bases (e.g., KEGG, Reactome, HumanCyc).
Standardized data structure, gene IDs, and chemical IDs across all incorporated databases.
Performed a consistency analysis among the ten knowledge bases prior to integration into GINv2.0.

Main Results:

Successfully integrated molecular interaction data from ten diverse human knowledge bases into GINv2.0.
GINv2.0 enables comprehensive systems-level analyses of biological pathways.
Analysis using GINv2.0 revealed coordinated regulation between glycolysis and autophagy, particularly under glucose starvation conditions.

Conclusions:

GINv2.0 represents a significant advancement in creating a unified resource for human molecular interaction data.
The expanded scope and enhanced capabilities of GINv2.0 offer a valuable tool for systems biology research.
The findings highlight coordinated regulatory mechanisms between key metabolic and cellular processes under specific nutrient conditions.