Graph Neural Networks for the Prediction of Protein-Protein Interfaces. - Niccolò Pancino; Alberto Rossi; Giorgio Ciano; Giorgia Giacomini; Simone Bonechi; Paolo Andreini; Franco Scarselli; Monica Bianchini; Pietro Bongini (ESANN, 2020)

Deep Learning Techniques for Dragonfly Action Recognition. - Martina Monaci; Niccolò Pancino; Paolo Andreini; Simone Bonechi; Pietro Bongini; Alberto Rossi; Giorgio Ciano; Giorgia Giacomini; Franco Scarselli; Monica Bianchini (ICPRAM, 2020)

CaregiverMatcher: graph neural networks for connecting caregivers of rare disease patients. - Filippo Guerranti; Mirco Mannino; Federica Baccini; Pietro Bongini; Niccolò Pancino; Anna Visibelli; Sara Marziali (KES, 2021)

A Deep Learning approach for oocytes segmentation and analysis. - Paolo Andreini; Niccolò Pancino; Filippo Costanti; Gabriele Eusepi; Barbara Toniella Corradini (ESANN, 2022)

A Neural Network Approach for the Analysis of Reproducible Ribo-Seq Profiles. - Giorgia Giacomini; Caterina Graziani; Veronica Lachi; Pietro Bongini; Niccolò Pancino; Monica Bianchini; Davide Chiarugi; Angelo Valleriani; Paolo Andreini (Algorithms, 2022)

GNNkeras: A Keras-based library for Graph Neural Networks and homogeneous and heterogeneous graph processing. - Niccolò Pancino; Pietro Bongini; Franco Scarselli; Monica Bianchini (SoftwareX, 2022)

A Deep Learning Approach to the Prediction of Drug Side-Effects on Molecular Graphs. - Pietro Bongini; Elisa Messori; Niccolò Pancino; Monica Bianchini (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Modular Multi-Source Prediction of Drug Side-Effects With DruGNN. - Pietro Bongini; Franco Scarselli; Monica Bianchini; Giovanna Maria Dimitri; Niccolò Pancino; Pietro Lió (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

NeuraGED: A GNN estimation for Graph-Edit Distance. - Sara Bacconi; Filippo Costanti; Monica Bianchini; Niccolò Pancino; Pietro Bongini (KES, 2024)

Facial Segmentation in Deepfake Classification: a Transfer Learning Approach. - Marco Tanfoni; Elia Giuseppe Ceroni; Niccolò Pancino; Monica Bianchini; Marco Maggini (KES, 2024)

MOLGMP: A Markov approach for molecular graph generation with GNNs. - Benoit Goupil; Antonin Joly; Niccolò Pancino; Pietro Bongini; Franco Scarselli; Monica Bianchini (Neurocomputing, 2025)