AsthmaKGxE

AsthmaKGxE integrates genetic, pharmacogenetic, environmental, psychosocial, nutritional, and socio-economic data and literature into a knowledge graph to elucidate asthma-environment interactions.

Key Features:

• Hybrid Methodology for Graph-Based Modeling: Employs a hybrid approach to construct a knowledge graph by integrating genetic and pharmacogenetic data from diverse public databases and scientific literature.
• Focus on Environmental Interactions: Uses natural language processing to extract and catalog environmental, psychological, nutritional, and socio-economic factors from biomedical literature.
• Integration with Knowledge Graph: Integrates the most substantiated findings from the interaction catalog into the knowledge graph to provide environmental context for asthma-related relationships.
• Artificial Intelligence Applications: Supports AI-driven analyses to identify associations such as stress, allergens, and obesity within the knowledge graph.

Scientific Applications:

• Pathophysiology and Etiology Insights: Maps interactions among genetic, pharmacogenetic, and environmental factors to provide insights into asthma mechanisms.
• Research and Development: Serves as a resource for researchers investigating environmental triggers and modifiers to guide targeted intervention development.
• Public Health Strategies: Informs public health analyses aimed at mitigating asthma prevalence through environmental and lifestyle factor assessment.

Methodology:

Hybrid construction of a knowledge graph integrating genetic and pharmacogenetic data from diverse public sources; natural language processing to extract and catalog asthma-environment interactions (environmental, psychological, nutritional, and socio-economic factors) from biomedical literature; integration of the most substantiated catalog findings into the knowledge graph; and support for AI-driven analyses to identify associations such as stress, allergens, and obesity.