Gut Microbiota Responses to Resistant Starch Across 586 Samples from Multiple Cohorts

586 paired fecal samples from healthy adults across multiple independent cohorts undergoing resistant starch dietary interventions. The dataset, authored by Biao Dong and last updated in May 2026, analyzes gut microbiota composition to identify reproducible microbial responses and their potential clinical relevance in inflammatory bowel disease.

Use Cases

• Training machine learning classifiers to discriminate between dietary intervention groups based on microbial profiles mentioned in the description.
• Identifying co-occurrence networks of microbial taxa that respond consistently to resistant starch supplementation.
• Validating candidate microbial biomarkers for inflammatory bowel disease by cross-referencing with enrichment patterns described.
• Analyzing predicted functional changes in carbohydrate-active enzymes (CAZymes) in response to dietary fiber.

Strengths

• Includes 586 paired fecal samples, providing a substantial sample size for analysis.
• Data is processed through a unified bioinformatics pipeline across multiple cohorts to minimize technical variability.
• Findings are validated against eight independent inflammatory bowel disease cohorts for clinical relevance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• The dataset is very small (14.3 KB), suggesting it may contain summary or processed results rather than raw sequence data.

Provenance

Source

figshare

Collection Method

Gut microbiota composition analysis from fecal samples collected during dietary interventions.

Time Range

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Freshness

Last updated 2026-05-20 05:44:16; freshness should be verified.

Geography

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