Matteo Barberis

This study minimizes the yeast cell cycle gene set using synthetic genomics, identifying minimal gene combinations that maintain viability and robustness across conditions.

This study identifies Pfk2p as an ATP-dependent RNA unwinding enzyme that modulates cell cycle progression by promoting translation of mitotic genes.

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

The paper identifies 68 potential drug targets for three autoimmune diseases by integrating genome-scale metabolic models with gene expression data and in vitro validation.

The paper develops a multi-scale model of CD4+ T cells integrating multiple modeling approaches to predict switch-like and oscillatory behaviors in inflammatory responses.

The paper models the ROS regulatory network to show how its dysfunction contributes to age-related diseases like Parkinson's and suggests potential therapeutic interventions.