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MMiKG: a knowledge graph-based platform for path mining of microbiota–mental diseases interactions.

Authors :
Sun, Haoran
Song, Zhaoqi
Chen, Qiuming
Wang, Meiling
Tang, Furong
Dou, Lijun
Zou, Quan
Yang, Fenglong
Source :
Briefings in Bioinformatics; Nov2023, Vol. 24 Issue 6, p1-9, 9p
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14675463
Volume :
24
Issue :
6
Database :
Complementary Index
Journal :
Briefings in Bioinformatics
Publication Type :
Academic Journal
Accession number :
173782091
Full Text :
https://doi.org/10.1093/bib/bbad340