Marco Rota Negroni

This study benchmarks three copy number signature compendia across cancers, showing their distinct predictability from multi-omic data and highlighting framework-dependent performance.

The paper introduces an AI-driven pipeline using Protein Language Models to discover hidden CLE peptides in plant proteomes, achieving high classification accuracy and identifying previously unannotated candidates.