Giovanni Minervini

The paper identifies cryptic phosphosites in the human proteome that are buried in the protein core and may influence folding and degradation, with implications for cancer.

This study uses a mathematical model combined with OCTA images to simulate tumor-induced angiogenesis in retinal hemangioblastoma, revealing critical insights into the timing and dynamics of vascular development.

The paper evaluates 43 methods for predicting intrinsically disordered regions and binding regions in proteins, finding that deep learning methods outperform older physicochemical approaches but binding prediction remains challenging.

The paper evaluates hydroxylation site predictors using independent datasets, finding they perform no better than random, highlighting issues with self-reported performance and generalization.