| Graph Neural Networks for the Prediction of Protein-Protein Interfaces. N Pancino, A Rossi, G Ciano, G Giacomini, S Bonechi, P Andreini, ... ESANN, 127-132, 2020 | 28 | 2020 |
| Modular multi–source prediction of drug side–effects with DruGNN P Bongini, F Scarselli, M Bianchini, GM Dimitri, N Pancino, P Lio IEEE/ACM Transactions on Computational Biology and Bioinformatics 20 (2 …, 2022 | 21 | 2022 |
| GNNkeras: A Keras-based library for Graph Neural Networks and homogeneous and heterogeneous graph processing N Pancino, P Bongini, F Scarselli, M Bianchini SoftwareX 18, 101061, 2022 | 16 | 2022 |
| BioGNN: how graph neural networks can solve biological problems P Bongini, N Pancino, F Scarselli, M Bianchini Artificial Intelligence and Machine Learning for Healthcare: Vol. 1: Image …, 2022 | 15 | 2022 |
| A mixed statistical and machine learning approach for the analysis of multimodal trail making test data N Pancino, C Graziani, V Lachi, ML Sampoli, E Ștefǎnescu, M Bianchini, ... Mathematics 9 (24), 3159, 2021 | 8 | 2021 |
| CaregiverMatcher: Graph neural networks for connecting caregivers of rare disease patients F Guerranti, M Mannino, F Baccini, P Bongini, N Pancino, A Visibelli, ... Procedia Computer Science 192, 1696-1704, 2021 | 8 | 2021 |
| A neural network approach for the analysis of reproducible ribo–seq profiles G Giacomini, C Graziani, V Lachi, P Bongini, N Pancino, M Bianchini, ... Algorithms 15 (8), 274, 2022 | 7 | 2022 |
| Drug side effect prediction with deep learning molecular embedding in a graph-of-graphs domain N Pancino, Y Perron, P Bongini, F Scarselli Mathematics 10 (23), 4550, 2022 | 5 | 2022 |
| Deep Learning Techniques for Dragonfly Action Recognition. M Monaci, N Pancino, P Andreini, S Bonechi, P Bongini, A Rossi, G Ciano, ... ICPRAM, 562-569, 2020 | 5 | 2020 |
| A Deep Learning Approach to the Prediction of Drug Side–Effects on Molecular Graphs P Bongini, E Messori, N Pancino, M Bianchini IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023 | 3 | 2023 |
| A Deep Learning approach for oocytes segmentation and analysis. P Andreini, N Pancino, F Costanti, G Eusepi, BT Corradini ESANN, 2022 | 3 | 2022 |
| A deep learning approach to the prediction of drug side-effects on molecular graphs P Bongini, E Messori, N Pancino, M Bianchini arXiv preprint arXiv:2211.16871, 2022 | 2 | 2022 |
| Blinking Rate Comparison Between Patients with Chronic Pain and Parkinson's Disease E Stefanescu, N Pancino, C Graziani, V Lachi, M Sampoli, G Dimitri, ... EUROPEAN JOURNAL OF NEUROLOGY 29, 669-669, 2022 | 2 | 2022 |
| Point-Wise Ribosome Translation Speed Prediction with Recurrent Neural Networks P Bongini, N Pancino, V Lachi, C Graziani, G Giacomini, P Andreini, ... Mathematics 12 (3), 465, 2024 | 1 | 2024 |
| Graph Neural Networks for Advanced Molecular Data Analysis N Pancino | 1 | 2023 |
| Generated or Not Generated (GNG): The Importance of Background in the Detection of Fake Images M Tanfoni, EG Ceroni, S Marziali, N Pancino, M Maggini, M Bianchini Electronics 13 (16), 3161, 2024 | | 2024 |
| Protein–Protein Interfaces: A Graph Neural Network Approach N Pancino, C Gallegati, F Romagnoli, P Bongini, M Bianchini International Journal of Molecular Sciences 25 (11), 5870, 2024 | | 2024 |
| Composite Graph Neural Networks for Molecular Property Prediction P Bongini, N Pancino, A Bendjeddou, F Scarselli, M Maggini, M Bianchini Int. J. Mol. Sci 25, 6583, 2024 | | 2024 |
Pietro BonginiPost Doctoral Student/Researcher, University of SienaEmail verificata su unisi.it
