2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.ET2026★ 1 cited
A Physically-Informed Subgraph Isomorphism Approach to Molecular Docking Using Quantum Annealers
Francesco Micucci, Matteo Barbieri, Gabriella Bettonte +6
Molecular docking is a crucial step in the development of new drugs as it guides the positioning of a small molecule (ligand) within the pocket of a target protein. In the literatu…
q-bio.BM2022★ 2 cited
GENEOnet: A new machine learning paradigm based on Group Equivariant Non-Expansive Operators. An application to protein pocket detection
Giovanni Bocchi, Patrizio Frosini, Alessandra Micheletti +5
Nowadays there is a big spotlight cast on the development of techniques of explainable machine learning. Here we introduce a new computational paradigm based on Group Equivariant N…