Ania-Ariadna Baetica

This paper analyzes the sensitivity of biological feedback circuits to parameter variations and identifies fundamental trade-offs in their robustness.

This paper introduces two Bayesian inference methods for stochastic gene expression parameters using multifidelity models, showing significant computational speedup compared to full FSP approaches.

This paper provides design guidelines for stable and effective sequestration feedback networks in synthetic biology.

The paper analyzes sequestration feedback systems using control theory to identify performance limits and tradeoffs in biological feedback mechanisms.

The paper uses Bayesian inference to assess context dependence of parameters in an E. coli growth control circuit across different experimental conditions.

This paper designs a synthetic control circuit to regulate population size and strain ratio in microbial consortia using dual feedback control.

The paper develops a Bayesian method to infer chemical signal timing and amplitude from population-level response distributions in a temporal logic gate system in E. coli.