ReGAIN: a bioinformatics platform for assessing probabilistic co-occurrence between resistance genes in bacterial pathogens.

ReGAIN reveals probabilistic dependencies among resistance genes in ESKAPEE pathogens, identifying both known and novel co-occurrence patterns.

• Why it matters: Understanding how resistance determinants co-occur is crucial for tracking multidrug resistance spread and informing effective surveillance and intervention strategies.
• What they did: The platform applies Bayesian network structure learning to analyze genomic data from bacterial populations, providing conditional probabilities, risks, and confidence intervals for gene relationships.
• The result: ReGAIN successfully recapitulates established gene associations and uncovers new candidate patterns, enabling scalable, reproducible analysis for epidemiology, genomics, and resistance management.