PODDA, MARCO Statistiche

PODDA, MARCO  

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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
Explaining Graph Classifiers by Unsupervised Node Relevance Attribution 1-gen-2024 Fontanesi, Michele; Micheli, Alessio; Podda, Marco
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.
A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor 1-gen-2018 Podda, Marco; Bacciu, Davide; Micheli, Alessio; Bellù, Roberto; Placidi, Giulia; Gagliardi, Luigi
Human leukocyte antigen polymorphisms in Italian primary biliary cirrhosis: a multicenter study of 664 patients and 1992 healthy controls 1-gen-2008 Italian PBC Genetic Study, Group; Podda, M; Gershwin, Me; Seldin, Mf; Qi, L; Muratori, L; Fabris, L; Marzioni, M; Rosina, F; Almasio, P; Alvaro, D; Floreani, A; Frison, S; Poli, F; Selmi, C; Invernizzi PAndreoletti, M; Andriulli, A; Baldini, V; Battezzati, Pm; Benedetti, A; Bernuzzi, F; Bianchi, Fb; Bianchi, I; Bignotto, M; Bragazzi, Mc; Brunetto, M; Caimi, M; Caliari, L; Caporaso, N; Casella, G; Casiraghi, A; Colli, A; Colombo, M; Conte, D; Croce, L; Crosignani, A; Dottorini, L; Ferrari, C; Fraquelli, M; Frati, Ce; Galli, A; Lleo, A; Mancino, Mg; Mandelli, G; Marra, F; Montanari, R; Monti, V; Morini, L; Morisco, F; Niro, G; Palasciano, G; Calmieri, Vo; Pasini, S; Picciotto, A; Portincasa, P; Pozzoli, V; Spinzi, Cinzia Giacinta; Strazzabosco, M; Tiribelli, C; Toniutto, P; Zerminai, P; Zuin, M.