Daniele De Martino

This paper develops a dynamical maximum entropy framework to model single-cell metabolic states during E. coli diauxie, revealing co-consumption as a continuous rather than discrete phenomenon.

This paper introduces a simulation platform to model how regulation and agency emerge in protocell ecologies under prebiotic conditions.

This paper introduces an unbiased method for metabolic flux inference by integrating thermodynamic constraints and 13C labeling data, revealing novel flux patterns in budding yeast.

This study quantifies the regulatory cost of cellular growth control using a Maximum Entropy approach in E. coli and human cells, showing different regulatory strategies and linking inverse temperature to growth dynamics.