Predicting the relationships between gut microbiota and mental disorders with knowledge graphs
Published in Health Information Science and Systems, 2020
This study constructs MiKG4MD, a knowledge graph that systematically organizes research on gut microbiota, neurotransmitters, and mental disorders. While most studies examine these relationships separately, MiKG4MD integrates dispersed findings into a structured knowledge base to identify and predict potential links. The graph is extendable, allowing integration with ontologies such as UMLS, MeSH, and KEGG. Performance is demonstrated using three SPARQL query test cases, showing that MiKG4MD effectively predicts gut microbiota-mental disorder relationships. This work highlights the importance of structured knowledge representation in advancing research on the gut-brain axis.
Recommended citation: Liu, T., Pan, X., Wang, X., Feenstra, K. A., Heringa, J., & Huang, Z. (2021). Predicting the relationships between gut microbiota and mental disorders with knowledge graphs. Health information science and systems, 9, 1-9.
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