ReGAIN provides a queryable database for investigating resistance gene co-occurrence in bacterial pathogens. The dataset, created by Elijah Bring Horvath and last updated in May 2026, uses Bayesian network structure learning to map relationships between resistance genes and optionally includes stress, heavy metal resistance, and virulence determinants. It is a 17.0 MB collection of CSV and HTML files.
Use Cases
- Analyze organism-specific patterns of resistance gene co-occurrence based on the described Bayesian network structure.
- Enrich resistome analyses by investigating the complex interplay of resistance genes mentioned in the description.
- Study co-occurrence patterns among stress, heavy metal resistance, and virulence gene determinants as an optional feature of the platform.
Strengths
- Dataset size is 17.0 MB, indicating a manageable download and analysis footprint.
- Includes an optional extension to analyze co-occurrence with stress, heavy metal resistance, and virulence genes.
- License is CC-BY-4.0, permitting flexible reuse with attribution.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
Provenance
- Source
- figshare
- Collection Method
- Likely generated by the ReGAIN command-line platform using Bayesian network structure learning on genomic data.
- Time Range
- null
- Freshness
- Last updated 2026-05-04 20:37:18; freshness should be verified.
- Geography
- null