ReviewMicrobiome2019
Challenges in the construction of knowledge bases for human microbiome-disease associations.
Review in Microbiome, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Maternal exposures and the infant gut microbiome: a systematic review with meta-analysis.Gut microbesPooled it
- Advancing Whole-Person Health through Informatics: A Narrative Review of Knowledge Resources for Complementary and Integrative Health.The Journal of nutrition · 2026Review
- DiMB-RE: mining the scientific literature for diet-microbiome associations.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Hypothesizing mechanistic links between microbes and disease using knowledge graphs.Scientific reports · 2025Article
- The gut microbiome as a modulator of arterial function and age-related arterial dysfunction.American journal of physiology. Heart and circulatory physiology · 2024Review
- Recent advances in deep learning and language models for studying the microbiome.Frontiers in genetics · 2024Review
- Leveraging pre-trained language models for mining microbiome-disease relationships.BMC bioinformatics · 2023Article
- KG-Hub-building and exchanging biological knowledge graphs.Bioinformatics (Oxford, England) · 2023Article
- Dietary Efficacy Evaluation by Applying a Prediction Model Using Clinical Fecal Microbiome Data of Colorectal Disease to a Controlled Animal Model from an Obesity Perspective.Microorganisms · 2022Review
- Machine-learning algorithms for asthma, COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects.Experimental & molecular medicine · 2022Article
- The Emerging Role of the Gut Microbiome in Cardiovascular Disease: Current Knowledge and Perspectives.Biomedicines · 2022Review
- Can manipulation of gut microbiota really be transformed into an intervention strategy for cardiovascular disease management?Folia microbiologica · 2021Review
- Reporting guidelines for human microbiome research: the STORMS checklist.Nature medicine · 2021Review
- Peryton: a manual collection of experimentally supported microbe-disease associations.Nucleic acids research · 2021Article
- Current Concepts, Opportunities, and Challenges of Gut Microbiome-Based Personalized Medicine in Nonalcoholic Fatty Liver Disease.Cell metabolism · 2021Review
- Article
- CoMNRank: An integrated approach to extract and prioritize human microbial metabolites from MEDLINE records.Journal of biomedical informatics · 2020Article
- Impact of host genetics on gut microbiome: Take-home lessons from human and mouse studies.Animal models and experimental medicine · 2020Review
- Knowledge-Based Biomedical Data Science.Annual review of biomedical data science · 2020Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The last few years have seen tremendous growth in human microbiome research, with a particular focus on the links to both mental and physical health and disease. Medical and experimental settings provide initial sources of information about these links, but individual studies produce disconnected pieces of knowledge bounded in context by the perspective of expert researchers reading full-text publications. Building a knowledge base (KB) consolidating these disconnected pieces is an essential first step to democratize and accelerate the process of accessing the collective discoveries of human disease connections to the human microbiome. In this article, we survey the existing tools and development efforts that have been produced to capture portions of the information needed to construct a KB of all known human microbiome-disease associations and highlight the need for additional innovations in natural language processing (NLP), text mining, taxonomic representations, and field-wide vocabulary standardization in human microbiome research. Addressing these challenges will enable the construction of KBs that help identify new insights amenable to experimental validation and potentially clinical decision support.
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What OpenQuestion holds
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.