Alberto Carignano

The paper designs modular yeast consortia for synthetic biology, showing that consortia dynamics can be predicted from individual strain models and optimized to achieve target behaviors.

This study investigates how microRNA-mediated incoherent feedforward loops suppress extrinsic noise, showing that translational inhibition expands noise rejection regimes and can buffer or amplify gene product fluctuations depending on time scales.

The paper models how optimal peptide filtering by antigen-presenting cells affects the timing of T-cell detection, finding an optimal filtering range influenced by MHC properties.

This paper introduces PIPER, a method to identify gene network perturbations in single-cell RNA-seq data, showing it outperforms existing methods on simulated data and identifies known regulators in real datasets.