Scott A. Rice

This paper develops a machine learning framework to predict symptomatic and asymptomatic bacteriuria in spinal cord injury patients using microbiome data, achieving high accuracy in classification.

This study identifies transcriptional changes in E. coli biofilms exposed to plasma-activated water, revealing key genes and pathways involved in their survival and response to oxidative stress.

The paper analyzes the complete genome of an ocular Pseudomonas aeruginosa isolate to identify accessory genes contributing to virulence and antibiotic resistance.