J. B. Rattray

The paper shows that the las and rhl quorum sensing systems in Pseudomonas aeruginosa interact reciprocally and cooperatively, enhancing their responsiveness to environmental changes.

This study investigates how quorum-sensing (QS) in Pseudomonas aeruginosa responds to genetic and signal perturbations, showing robustness in density-dependent gene expression despite signal supplementation or synthase knockouts.

This paper uses deep learning to classify Pseudomonas aeruginosa strains based on colony morphology, achieving high accuracy despite limited data.

This study shows Pseudomonas aeruginosa uses quorum sensing to produce graded and bimodal responses to population density changes, without a clear threshold for gene expression activation.

The paper uses agent-based simulations to study how environmental factors shape the evolution of quorum-sensing strategies in bacteria, revealing how genetic constraints influence cooperation and resilience against cheaters.