Alexis M. Hill

The paper develops a mathematical model of translation incorporating tRNA dynamics and re-charging to show that codon usage optimizes protein synthesis depending on tRNA availability.

The paper develops a stochastic gene expression model to quantify how codon usage bias affects burden and yield during protein overexpression in bacteria, finding an overoptimization domain that reduces yield.

This study constructs a computational model of bacteriophage φX174 gene regulation and shows that canonical promoters and terminators suffice to explain transcript abundance variation.

The paper identifies new CRISPR-associated transposons (CASTs) by analyzing metagenomic databases, revealing novel architectures and systems that co-opt different CRISPR-Cas effectors.

The paper demonstrates that complex gene expression patterns can be achieved in bacteriophage genomes by adjusting promoter, terminator, and RNase cleavage site placements and strengths without dedicated regulatory genes.