ArticleScientific reports2022
Towards a knowledge graph for pre-/probiotics and microbiota-gut-brain axis diseases.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- KG-Microbe: Building modular and scalable knowledge graphs for microbiome and microbial sciences.GigaScience · 2026Article
- Microbiome knowledge graph as a tool to understand bacteria-host associations.Archives of microbiology · 2025Article
- Mining literature and pathway data to explore the relations of ketamine with neurotransmitters and gut microbiota using a knowledge-graph.Bioinformatics (Oxford, England) · 2024Article
- Integrating biological knowledge for mechanistic inference in the host-associated microbiome.Frontiers in microbiology · 2024Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scientific publications present biological relationships but are structured for human reading, making it difficult to use this resource for semantic integration and querying. Existing databases, on the other hand, are well structured for automated analysis, but do not contain comprehensive biological knowledge. We devised an approach for constructing comprehensive knowledge graphs from these two types of resources and applied it to investigate relationships between pre-/probiotics and microbiota-gut-brain axis diseases. To this end, we created (i) a knowledge base, dubbed ppstatement, containing manually curated detailed annotations, and (ii) a knowledge base, called ppconcept, containing automatically annotated concepts. The resulting Pre-/Probiotics Knowledge Graph (PPKG) combines these two knowledge bases with three other public databases (i.e. MeSH, UMLS and SNOMED CT). To validate the performance of PPKG and to demonstrate the added value of integrating two knowledge bases, we created four biological query cases. The query cases demonstrate that we can retrieve co-occurring concepts of interest, and also that combining the two knowledge bases leads to more comprehensive query results than utilizing them separately. The PPKG enables users to pose research queries such as "which pre-/probiotics combinations may benefit depression?", potentially leading to novel biological insights.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.