Paul A. Jensen

This paper quantifies the limitations of drug-blind prediction in cancer DRP models, showing that generalization relies on mechanistic overlap and that performance is more about dataset behavior than model behavior.

The paper presents an optimization framework for coordinating multiple liquid handling robots to plan and schedule biological experiments efficiently.

This study identifies the MutRS quorum sensing system as a regulator of lantibiotic mutacin production in Streptococcus mutans and shows its role in inter- and intrastrain crosstalk.

The paper analyzes bacteriology literature and finds that ten species account for half of all research, leaving 74% of species unstudied.

This paper identifies Streptococcin B as a bacteriocin produced during the early competence cascade in S. pneumoniae, which enhances intraspecies competition by targeting non-competent and ComE-deleted strains.

The paper optimizes an rRNA depletion protocol using statistical design of experiments, resulting in more efficient rRNA removal, lower reagent use, and reduced cost.

This paper introduces a reinforcement learning framework, OligoRL, for solving complex oligonucleotide design problems and demonstrates its application to three specific design tasks.

The paper introduces a method for efficient random sampling from convex and non-convex constraint-based models, focusing on under-sampled regions.

The paper constructs a genome-scale metabolic model of Streptococcus mutans and validates it against experimental data, showing high accuracy in predicting nutrient requirements and gene essentiality.

The paper introduces three algorithms to improve flux coupling analysis in genome-scale metabolic models, enhancing efficiency and biological interpretability.