45 citations · 63 across the 13 of their papers we have counts for
14 papers
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…
GENEOnet: Statistical analysis supporting explainability and trustworthiness
Giovanni Bocchi, Patrizio Frosini, Alessandra Micheletti +5
Group Equivariant Non-Expansive Operators (GENEOs) have emerged as mathematical tools for constructing networks for Machine Learning and Artificial Intelligence. Recent findings su…
Molecular Docking via Weighted Subgraph Isomorphism on Quantum Annealers
Emanuele Triuzzi, Riccardo Mengoni, Francesco Micucci +4
Molecular docking is an essential step in the drug discovery process involving the detection of three-dimensional poses of a ligand inside the active site of the protein. In this p…
ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening
Gianmarco Accordi, Davide Gadioli, Giorgio Seguini +2
Virtual screening is a technique used in drug discovery to select the most promising molecules to test in a lab. To perform virtual screening, we need a large set of molecules as i…
A LSTM-enhanced surrogate model to simulate the dynamics of particle-laden fluid systems
Arash Hajisharifi, Rahul Halder, Michele Girfoglio +3
The numerical treatment of fluid-particle systems is a very challenging problem because of the complex coupling phenomena occurring between the two phases. Although accurate mathem…
Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach
Gianluca Palermo, Gianmarco Accordi, Davide Gadioli +32
Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer…