ArticleScientific reports2016
Gene expression profiling gut microbiota in different races of humans.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
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Who cites it
53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 88 citations in OpenAlex.
- The Prognostic Value of Tumor-Associated Neutrophils in Colorectal Cancer: A Systematic Review and Meta-Analysis.Cancer medicine · 2025Pooled it
- Effect of potassium-competitive acid blockers on human gut microbiota: a systematic review and meta-analysis.Frontiers in pharmacology · 2023Pooled it
- Microflora: a promising potential in the diagnosis and treatment of non-small cell lung cancer.International journal of clinical oncology · 2026Review
- The ethnicity and gut microbiota hypothesis: analyzing multifactorial interactions and their health implications.Frontiers in microbiology · 2026Review
- Decoding the reproductive microbiome: enabling clinical and biological insights through machine and deep learning.Frontiers in endocrinology · 2026Review
- Scoping Review of Microbiota Dysbiosis and Risk of Preeclampsia.American journal of reproductive immunology (New York, N.Y. : 1989) · 2024Article
- Gut Dysbiosis in Patients With Fontan Circulation.Journal of the American Heart Association · 2024Article
- Metastasis and the Microbiome: The Impact of Bacteria in Disseminated Colorectal Cancer.Frontiers in bioscience (Landmark edition) · 2024Review
- Comparison of gut microbiota profiles between patients suffering from elderly frailty syndrome and non-frail elderly individuals.Molecular biology reports · 2024Article
- Association between Mild Cognitive Impairment and Gut Microbiota in Elderly Korean Patients.Journal of microbiology and biotechnology · 2023Article
- Emerging Relationship between the Gut Microbiome and Prostate Cancer.The world journal of men's health · 2023Review
- Differential bumble bee gene expression associated with pathogen infection and pollen diet.BMC genomics · 2023Article
- Effects of Silage Diet on Meat Quality through Shaping Gut Microbiota in Finishing Pigs.Microbiology spectrum · 2023Article
- Trait-Based Method of Quantitative Assessment of Ecological Functional Groups in the Human Intestinal Microbiome.Biology · 2023Article
- Identifying microbial signatures for patients with postmenopausal osteoporosis using gut microbiota analyses and feature selection approaches.Frontiers in microbiology · 2023Article
- Association of Habitual Intake of Probiotic Supplements and Yogurt with Characteristics of the Gut Microbiome in the Multiethnic Cohort Adiposity Phenotype Study.Gut microbiome (Cambridge, England) · 2023Article
- Toxin-linked mobile genetic elements in major enteric bacterial pathogens.Gut microbiome (Cambridge, England) · 2023Review
- Machine learning approaches in microbiome research: challenges and best practices.Frontiers in microbiology · 2023Review
- Proton pump inhibitor usage associates with higher risk of first episodes of pneumonia and peritonitis in peritoneal dialysis patients.Renal failure · 2022Article
- Characteristics of the Gut Bacterial Composition in People of Different Nationalities and Religions.Microorganisms · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome.
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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.