Mathieu Clément‐Ziza

The paper identifies a central state transition in yeast molecular networks linked to PKA and TOR signaling, showing how genetic variants can cause global or local molecular changes affecting multiple cellular traits.

This study integrates transcriptome, proteome, and phosphoproteome data from yeast to show how genetic variation affects molecular networks and cellular growth traits, with phosphorylation playing a key role.

This paper develops three methods to detect epistasis using Random Forest, outperforming existing approaches in simulated and real yeast datasets.