ArticleFrontiers in microbiology2021
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.
Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 3 of them syntheses that pooled it.
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
61 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Meta-analysis of 22,710 human microbiome metagenomes defines an oral-to-gut microbial enrichment score and associations with host health and disease.Nature communications · 2025Pooled it
- Breast cancer and microbiome: a systematic review highlighting challenges for clinical translation.BMC women's health · 2025Pooled it
- Host phenotype classification from human microbiome data is mainly driven by the presence of microbial taxa.PLoS computational biology · 2022Pooled it
- Reconstructing community dynamics from limited observations.Microbiome · 2026Article
- AI-empowered human microbiome research.Gut · 2026Review
- Mapping the Convergence of Frontier Technologies for Major Environmental Challenges: A Chemical and Molecular Perspective on the Use of AI for Climate Action and Antimicrobial Resistance.Molecules (Basel, Switzerland) · 2026Review
- Gut microbial profiles of COVID-19 patients in Uganda.African health sciences · 2026Article
- Artificial intelligence in functional food innovation: Bioactive enhancement and formulation optimization: A quasi-systematic review.Food chemistry: X · 2026Review
- Transformer Models, Graph Networks, and Generative AI in Gut Microbiome Research: A Narrative Review.Bioengineering (Basel, Switzerland) · 2026Review
- Integrated multi-omics analysis unveils microbiota-metabolite-host interactions and novel biomarkers for early diabetic kidney disease diagnosis.Frontiers in immunology · 2026Article
- Early-life microbiome trajectories as biomarkers to predict health outcomes.Microbiome research reports · 2026Review
- Improving DirectLiNGAM for high-dimensional microbiome data: roots screening and eBIC based model selection.Frontiers in systems biology · 2026Article
- HoloFoodR: a statistical programming framework for holo-omics data integration workflows.Bioinformatics (Oxford, England) · 2025Article
- The Gut Microbiome and Its Impact on Mood and Decision-Making: A Mechanistic and Therapeutic Review.Nutrients · 2025Review
- Optimizing breast cancer chemotherapy by harnessing gut microbiota with insights from artificial intelligence.NPJ biofilms and microbiomes · 2025Review
- Controlling metabolic stability of food microbiome for stable indigenous liquor fermentation.NPJ biofilms and microbiomes · 2025Article
- Recent advances in therapeutic probiotics: insights from human trials.Clinical microbiology reviews · 2025Review
- Assessing the safety of microbiome perturbations.Microbial genomics · 2025Review
- Cross-validation for training and testing co-occurrence network inference algorithms.BMC bioinformatics · 2025Article
- EVOLVING TRENDS AND EMERGING THEMES IN GUT MICROBIOTA RESEARCH: A COMPREHENSIVE BIBLIOMETRIC ANALYSIS (2015-2024).Arquivos de gastroenterologia · 2025Article
1 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
39 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.
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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.