ReviewExperimental biology and medicine (Maywood, N.J.)2019
Mapping the microbial interactome: Statistical and experimental approaches for microbiome network inference.
Review in Experimental biology and medicine (Maywood, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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
24 citing papers in PubMed, 52 citations in OpenAlex.
- Effect ofNutrients · 2026Trial
- Article
- Linking complex microbial interactions and dysbiosis through a disordered Lotka-Volterra model.eLife · 2026Article
- Next-generation soil monitoring: linking metagenomics, biosensors, and ecological modeling for sustainable agriculture.Frontiers in microbiology · 2026Review
- Machine learning determines the incidence of Alzheimer's disease based on population gut microbiome profile.Brain communications · 2025Article
- The Role of Butyric Acid and Microorganisms in Chronic Inflammatory Diseases and Microbiome-Based Therapeutics.Journal of inflammation research · 2025Review
- Exploration of the Changes in Facial Microbiota of Maskne Patients and Healthy Controls Before and After Wearing Masks Using 16 S rRNA Analysis.Journal of epidemiology and global health · 2024Article
- Gut microbiome-metabolome interactions predict host condition.Microbiome · 2024Article
- Microbial biogeography of the eastern Yucatán carbonate aquifer.Applied and environmental microbiology · 2023Article
- Bakdrive: identifying a minimum set of bacterial species driving interactions across multiple microbial communities.Bioinformatics (Oxford, England) · 2023Article
- Connect the dots: sketching out microbiome interactions through networking approaches.Microbiome research reports · 2023Review
- A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors.Cell · 2022Article
- Article
- Article
- Diversity and Interactomics of Bacterial Communities Associated with Dominant Trees During Tropical Forest Recovery.Current microbiology · 2021Article
- Engineering the Microbiome to Prevent Adverse Events: Challenges and Opportunities.Annual review of pharmacology and toxicology · 2021Review
- Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions.Frontiers in microbiology · 2021Review
- Mathematical-based microbiome analytics for clinical translation.Computational and structural biotechnology journal · 2021Review
- Scientific Prospects for Cannabis-Microbiome Research to Ensure Quality and Safety of Products.Microorganisms · 2020Review
- Metabolite-mediated modelling of microbial community dynamics captures emergent behaviour more effectively than species-species modelling.Journal of the Royal Society, Interface · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
impact statementThis review provides a comprehensive description of experimental and statistical tools used for network analyses of the human gut microbiome. Understanding the system dynamics of microbial interactions may lead to the improvement of therapeutic approaches for managing microbiome-associated diseases. Microbiome network inference tools have been developed and applied to both cross-sectional and longitudinal experimental designs, as well as to multi-omic datasets, with the goal of untangling the complex web of microbe-host, microbe-environmental, and metabolism-mediated microbial interactions. The characterization of these interaction networks may lead to a better understanding of the systems dynamics of the human gut microbiome, augmenting our knowledge of the microbiome's role in human health, and guiding the optimization of effective, precise, and rational therapeutic strategies for managing microbiome-associated disease.
Indexed as
Identifiers
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.