Leonardo Di Bari

This paper introduces a coevolution-aware ancestral sequence reconstruction framework that improves reconstruction by incorporating residue-residue constraints from extant protein families.

This study compares three simulation schemes for modeling protein evolution, finding that population genetics dynamics best capture phylogenetic correlations and selective sweeps without requiring additional data.

The paper quantifies fluctuations in protein evolution by analyzing correlations between mutations and shows ancestral sequence properties influence evolutionary dynamics and reconstruction accuracy.

This paper introduces a data-driven epistatic model of protein evolution that reproduces sequence statistics across different time scales and uncovers the collective nature of epistasis.