Klas I. Udekwu

This study investigates how environmental variation affects DNA methylation patterns in bacteria, finding that methylation states depend on genomic position and growth rate.

This study examines spatial and temporal patterns in public transit aerobiomes across six global cities using shotgun metagenomics, revealing city-specific microbial signatures and the importance of bioinformatics pipelines for contaminant removal.

The paper develops an open-source computational platform to predict failures of sequential antibiotic therapy using collateral sensitivity and bacterial resistance profiles.

This study introduces a new metagenomic health index to assess microbiome health by focusing on functional potential rather than taxonomy, showing improved performance in distinguishing healthy from diseased states.

This paper uses control invariant sets to predict treatment failure in antibiotic cycling, aiming to reduce multi-drug resistant pathogen emergence.