PODDA, MARCO Statistiche
PODDA, MARCO
DIPARTIMENTO DI INFORMATICA
Classification of Neisseria meningitidis genomes with a bag-of-words approach and machine learning
2024-01-01 Podda, Marco; Bonechi, Simone; Palladino, Andrea; Scaramuzzino, Mattia; Brozzi, Alessandro; Roma, Guglielmo; Muzzi, Alessandro; Priami, Corrado; Sirbu, Alina; Bodini, Margherita
Classifier-Free Graph Diffusion for Molecular Property Targeting
2024-01-01 Ninniri, Matteo; Podda, Marco; Bacciu, Davide
Explaining Graph Classifiers by Unsupervised Node Relevance Attribution
2024-01-01 Fontanesi, Michele; Micheli, Alessio; Podda, Marco
How Much Do DNA and Protein Deep Embeddings Preserve Biological Information?
2024-01-01 Tolloso, Matteo; Galfre, Silvia Giulia; Pavone, Arianna; Podda, Marco; Sirbu, Alina; Priami, Corrado
Predictive machine learning model for mechanical dilatation in transvenous lead extraction procedures
2024-01-01 De Lucia, R; Micheli, A; Parlato, A; Podda, M; Pedrelli, L; Aliprandi, F; Parollo, M; Segreti, L; Di Cori, A; Canu, A; Grifoni, G; Barletta, V; Viani, S; Zucchelli, G
Deep Graph Networks for Drug Repurposing with Multi-Protein Targets
2023-01-01 Bacciu, Davide; Errica, Federico; Gravina, Alessio; Madeddu, Lorenzo; Podda, Marco; Stilo, Giovanni
Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs
2023-01-01 Fontanesi, Michele; Micheli, Alessio; Milazzo, Paolo; Podda, Marco
Graph Representation Learning
2023-01-01 Bacciu, Davide; Errica, Federico; Micheli, Alessio; Navarin, Nicolò; Pasa, Luca; Podda, Marco; Zambon, Daniele
Deep Learning in Cheminformatics
2022-01-01 Micheli, Alessio; Podda, Marco
Classification of Biochemical Pathway Robustness with Neural Networks for Graphs
2021-01-01 Podda, M.; Bove, P.; Micheli, A.; Milazzo, P.
Graphgen-redux: A Fast and Lightweight Recurrent Model for labeled Graph Generation
2021-01-01 Bacciu, D.; Podda, M.
In silico modeling of biochemical pathways
2021-01-01 Milazzo, Paolo; Gori, Roberta; Micheli, Alessio; Nasti, Lucia; Podda, Marco
A Deep Generative Model for Fragment-Based Molecule Generation
2020-01-01 Podda, M; Bacciu, D; Micheli, A
A Fair Comparison of Graph Neural Networks for Graph Classification
2020-01-01 Errica, Federico; Podda, Marco; Bacciu, Davide; Micheli, Alessio
A gentle introduction to deep learning for graphs
2020-01-01 Bacciu, D.; Errica, F.; Micheli, A.; Podda, M.
Biochemical pathway robustness prediction with graph neural networks
2020-01-01 Podda, M.; Bacciu, D.; Micheli, A.; Milazzo, P.
Edge-based sequential graph generation with recurrent neural networks
2020-01-01 Bacciu, D.; Micheli, A.; Podda, M.
Prediction of dynamical properties of biochemical pathways with graph neural networks
2020-01-01 Bove, P.; Micheli, A.; Milazzo, P.; Podda, M.
Graph generation by sequential edge prediction
2019-01-01 Bacciu, D.; Micheli, A.; Podda, M.
Preliminary Results on Predicting Robustness ofBiochemical Pathways through MachineLearning on Graphs
2019-01-01 Bove, P.; Micheli, A.; Milazzo, P.; Podda, M.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Classification of Neisseria meningitidis genomes with a bag-of-words approach and machine learning | 1-gen-2024 | Podda, Marco; Bonechi, Simone; Palladino, Andrea; Scaramuzzino, Mattia; Brozzi, Alessandro; Roma, Guglielmo; Muzzi, Alessandro; Priami, Corrado; Sirbu, Alina; Bodini, Margherita | |
| Classifier-Free Graph Diffusion for Molecular Property Targeting | 1-gen-2024 | Ninniri, Matteo; Podda, Marco; Bacciu, Davide | |
| Explaining Graph Classifiers by Unsupervised Node Relevance Attribution | 1-gen-2024 | Fontanesi, Michele; Micheli, Alessio; Podda, Marco | |
| How Much Do DNA and Protein Deep Embeddings Preserve Biological Information? | 1-gen-2024 | Tolloso, Matteo; Galfre, Silvia Giulia; Pavone, Arianna; Podda, Marco; Sirbu, Alina; Priami, Corrado | |
| Predictive machine learning model for mechanical dilatation in transvenous lead extraction procedures | 1-gen-2024 | De Lucia, R; Micheli, A; Parlato, A; Podda, M; Pedrelli, L; Aliprandi, F; Parollo, M; Segreti, L; Di Cori, A; Canu, A; Grifoni, G; Barletta, V; Viani, S; Zucchelli, G | |
| Deep Graph Networks for Drug Repurposing with Multi-Protein Targets | 1-gen-2023 | Bacciu, Davide; Errica, Federico; Gravina, Alessio; Madeddu, Lorenzo; Podda, Marco; Stilo, Giovanni | |
| Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs | 1-gen-2023 | Fontanesi, Michele; Micheli, Alessio; Milazzo, Paolo; Podda, Marco | |
| Graph Representation Learning | 1-gen-2023 | Bacciu, Davide; Errica, Federico; Micheli, Alessio; Navarin, Nicolò; Pasa, Luca; Podda, Marco; Zambon, Daniele | |
| Deep Learning in Cheminformatics | 1-gen-2022 | Micheli, Alessio; Podda, Marco | |
| Classification of Biochemical Pathway Robustness with Neural Networks for Graphs | 1-gen-2021 | Podda, M.; Bove, P.; Micheli, A.; Milazzo, P. | |
| Graphgen-redux: A Fast and Lightweight Recurrent Model for labeled Graph Generation | 1-gen-2021 | Bacciu, D.; Podda, M. | |
| In silico modeling of biochemical pathways | 1-gen-2021 | Milazzo, Paolo; Gori, Roberta; Micheli, Alessio; Nasti, Lucia; Podda, Marco | |
| A Deep Generative Model for Fragment-Based Molecule Generation | 1-gen-2020 | Podda, M; Bacciu, D; Micheli, A | |
| A Fair Comparison of Graph Neural Networks for Graph Classification | 1-gen-2020 | Errica, Federico; Podda, Marco; Bacciu, Davide; Micheli, Alessio | |
| A gentle introduction to deep learning for graphs | 1-gen-2020 | Bacciu, D.; Errica, F.; Micheli, A.; Podda, M. | |
| Biochemical pathway robustness prediction with graph neural networks | 1-gen-2020 | Podda, M.; Bacciu, D.; Micheli, A.; Milazzo, P. | |
| Edge-based sequential graph generation with recurrent neural networks | 1-gen-2020 | Bacciu, D.; Micheli, A.; Podda, M. | |
| Prediction of dynamical properties of biochemical pathways with graph neural networks | 1-gen-2020 | Bove, P.; Micheli, A.; Milazzo, P.; Podda, M. | |
| Graph generation by sequential edge prediction | 1-gen-2019 | Bacciu, D.; Micheli, A.; Podda, M. | |
| Preliminary Results on Predicting Robustness ofBiochemical Pathways through MachineLearning on Graphs | 1-gen-2019 | Bove, P.; Micheli, A.; Milazzo, P.; Podda, M. |