MMiKG: a knowledge graph-based platform for path mining of microbiota-mental diseases interactions
Haoran Sun1, Zhaoqi Song2, Qiuming Chen1
1School of Medical Imaging, Fujian Medical University, Fuzhou 350122, China.
Abstract:
The microbiota-gut-brain axis denotes a two-way system of interactions between the gut and the brain, comprising three key components: (1) gut microbiota, (2) intermediates and (3) mental ailments. These constituents communicate with one another to induce changes in the host's mood, cognition and demeanor. Knowledge concerning the regulation of the host central nervous system by gut microbiota is fragmented and mostly confined to disorganized or semi-structured unrestricted texts. Such a format hinders the exploration and comprehension of unknown territories or the further advancement of artificial intelligence systems. Hence, we collated crucial information by scrutinizing an extensive body of literature, amalgamated the extant knowledge of the microbiota-gut-brain axis and depicted it in the form of a knowledge graph named MMiKG, which can be visualized on the GraphXR platform and the Neo4j database, correspondingly. By merging various associated resources and deducing prospective connections between gut microbiota and the central nervous system through MMiKG, users can acquire a more comprehensive perception of the pathogenesis of mental disorders and generate novel insights for advancing therapeutic measures. As a free and open-source platform, MMiKG can be accessed at http://yangbiolab.cn:8501/ with no login requirement.
Insights
This study maps the microbiota-gut-brain axis, detailing interactions between gut microbes and the brain. The developed knowledge graph, MMiKG, aids understanding of mental disorders and therapeutic development.
Area of Science:
- Neuroscience
- Microbiology
- Computational Biology
Background:
- The microbiota-gut-brain axis describes bidirectional communication between the gut microbiota and the central nervous system.
- Existing knowledge on this axis is fragmented, hindering comprehensive understanding and AI development.
- This axis influences host mood, cognition, and behavior through complex interactions.
Purpose of the Study:
- To consolidate fragmented knowledge on the microbiota-gut-brain axis.
- To develop a structured knowledge graph (MMiKG) for visualizing and analyzing these interactions.
- To facilitate a deeper understanding of mental disorder pathogenesis and identify new therapeutic strategies.
Main Methods:
- Extensive literature review to collate information on the microbiota-gut-brain axis.
- Development of the Microbiota-Gut-Brain Axis Knowledge Graph (MMiKG).
- Utilizing GraphXR and Neo4j for visualization and data management.
Main Results:
- Creation of MMiKG, a comprehensive knowledge graph integrating diverse data resources.
- MMiKG enables visualization of connections between gut microbiota and the central nervous system.
- The platform facilitates exploration of potential links relevant to mental health.
Conclusions:
- MMiKG provides a unified platform for understanding the microbiota-gut-brain axis.
- The knowledge graph aids in comprehending mental disorder mechanisms.
- MMiKG offers novel insights for advancing therapeutic interventions and research in the field.
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