Francesco Craighero

The paper introduces Riboclette, a conditional deep learning model that predicts ribosome footprints under amino acid deprivation and identifies key codons and motifs driving translation stalling.

This study introduces RiboGL, a model combining graph and recurrent neural networks to predict ribosome density from mRNA secondary structure, outperforming existing methods.