Declan G. Bates

This study identifies design principles for engineering bacteria to maximize chemical production in batch cultures by optimizing gene expression and metabolic resource allocation.

gcFront identifies Pareto optimal growth-coupled cell factory designs by optimizing cell growth, product synthesis, and coupling strength using a genetic algorithm.

The paper designs an irreversible metabolic switch in E. coli to reduce inducer usage for scalable microbial chemical production.

This study investigates how growth rate and nutrient quality affect gene expression capacity in bacteria, showing that metabolism governs resource usage and that low growth in high-quality medium maximizes synthetic gene expression.

The paper develops a mechanistic model of the BLADE platform to predict performance of 256 synthetic DNA recombination circuits, showing good agreement with experimental data and identifying factors affecting circuit performance.

The paper designs and evaluates robust controllers for combined transcriptional and translational resource allocation in synthetic circuits, identifying performance trade-offs and promising architectures.

This paper presents minimally complex DNA-based control circuits for experimental implementation of feedback control systems in synthetic biology.

The paper develops a mechanistic model of gene expression and resource allocation to design controllers that restore modularity in synthetic gene circuits by dynamically allocating ribosomes.

The paper demonstrates how dynamic allocation of orthogonal ribosomes reduces ribosome-mediated gene coupling in synthetic circuits.