ReviewComputational and structural biotechnology journal2021
Network analysis methods for studying microbial communities: A mini review.
Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 163 papers, 2 of them syntheses 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
163 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Meta-analysis of microbiome association networks reveal patterns of dysbiosis in diseased microbiomes.Scientific reports · 2022Pooled it
- Bifidobacterium lactis Probio-M8 improves bone metabolism in patients with postmenopausal osteoporosis, possibly by modulating the gut microbiota.European journal of nutrition · 2023Trial
- CRISPR-Cas immune repertoires as an ecological record of bacterial interactions with mobile genetic elements in the human gut.Gut microbes · 2026Article
- Antioxidant and Anti-Inflammatory Effects of InhaledPlants (Basel, Switzerland) · 2026Article
- Metabolite-Resolved Validation of Bacterial Organophosphate Transformation in Soil: A Critical Review of Selected Organophosphate Case Studies.Microorganisms · 2026Review
- Bacterial-fungal interactions: connections and consequences.Essays in biochemistry · 2026Review
- Rice-crayfish farming mode drives distinct soil properties and ecological assembly of soil microbiome.Microbiology spectrum · 2026Article
- Article
- Article
- Caste-Associated Gut Microbial Diversity and Predicted Functional Profiles inInternational journal of molecular sciences · 2026Article
- Bacterial and fungal communities and network dynamics in Otitis media patients upon 1,8-Cineol treatment.NPJ systems biology and applications · 2026Article
- Diurnal dynamics of maize gene expression is associated with phyllosphere microbiome composition.International microbiology : the official journal of the Spanish Society for Microbiology · 2026Article
- The urinary microbiome, overactive bladder and bladder pain syndrome/interstitial cystitis - mechanisms, diagnostics and therapeutic opportunities.Nature reviews. Urology · 2026Review
- Differential co-occurrence analysis: a method to extract ecological modules from clinical microbiome data.mSystems · 2026Article
- Vaginal microbiome composition in pregnant and non-pregnant women: community structure, population variation, clinical impact, and metagenomics approaches.Infection and immunity · 2026Review
- Past subarctic marine food web shifts recovered by sedaDNA and network analysis.Scientific reports · 2026Article
- Remodelling of the gut virome after long-term fasting.NPJ biofilms and microbiomes · 2026Article
- Spatiotemporal Dynamics and Assembly Mechanisms of Bacterial Communities in Tropical-Subtropical Coastal Waters of the Leizhou Peninsula, China.Microorganisms · 2026Article
- Host genotype and environmental factors differentially shape the black piranha's gill microbiota.Microbiology spectrum · 2026Article
103 more citing papers are in PubMed but not listed here.
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
Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities in complex and contiguous environments. They engage in numerous inter- and intra- kingdom interactions which can be inferred from microbiome profiling data. In particular, network-based approaches have proven helpful in deciphering complex microbial interaction patterns. Here we give an overview of state-of-the-art methods to infer intra-kingdom interactions ranging from simple correlation- to complex conditional dependence-based methods. We highlight common biases encountered in microbial profiles and discuss mitigation strategies employed by different tools and their trade-off with increased computational complexity. Finally, we discuss current limitations that motivate further method development to infer inter-kingdom interactions and to robustly and comprehensively characterize microbial environments in the future.
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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.