Johan Pensar

PAN-GWES identifies co-selected and epistatic genomic variations in bacterial genomes using de Bruijn graphs to analyze drug resistance and adaptation traits.

immuneML provides an open-source ecosystem for reproducible and interoperable machine learning analysis of adaptive immune receptor repertoires, demonstrating its utility through benchmarking and novel methods.

This paper uses genome-wide co-evolution analysis to identify genomic rearrangements in Enterococcus faecium, linking them to adaptation to hospital environments.

This paper introduces SpydrPick, a model-free method to detect co-selection and epistasis in bacterial genomes, revealing both known and novel targets in human pathogens.

This study analyzes the genomes of Enterococcus faecium strains to understand their adaptive evolution, identifying plasmids as key indicators of host specificity through population-wide genomic analysis.

SuperDCA enables genome-wide epistasis analysis in bacteria by efficiently modeling interactions among polymorphisms, revealing novel biological insights in Streptococcus pneumoniae.