Here you can find a list of my scientific publications.
2024
Mastropietro, A., & Bajorath, J. (2024). Protocol to explain support vector machine predictions via exact Shapley value computation. STAR protocols, 5(2), 103010. https://doi.org/10.1016/j.xpro.2024.103010.
2023
Mastropietro, A., Pasculli, G. & Bajorath, J. Learning characteristics of graph neural networks predicting protein–ligand affinities. Nature Machine Intelligence 5(12), 1427–1436 (2023). https://doi.org/10.1038/s42256-023-00756-9. Read here: https://rdcu.be/dqZlS.
Mastropietro, A., Feldmann, C. & Bajorath, J. Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel. Scienfic Reports 13(1), 19561 (2023). https://doi.org/10.1038/s41598-023-46930-2.
Andrea Mastropietro, Gianluca De Carlo, Aris Anagnostopoulos, XGDAG: eXplainable Gene–Disease Associations via Graph Neural Networks, Bioinformatics, Volume 39, Issue 8, August 2023, btad482, https://doi.org/10.1093/bioinformatics/btad482
Paola Stolfi, Andrea Mastropietro, Giuseppe Pasculli, Paolo Tieri, Davide Vergni, NIAPU: network-informed adaptive positive-unlabeled learning for disease gene identification, Bioinformatics, Volume 39, Issue 2, February 2023, btac848, https://doi.org/10.1093/bioinformatics/btac84
2022
Mastropietro, A., Pasculli, G., & Bajorath, J. (2022). Protocol to explain graph neural network predictions using an edge-centric Shapley value-based approach. STAR Protocols, 3(4), 101887. https://doi:10.1016/j.xpro.2022.101887.
Mastropietro, A., Pasculli, G., Feldmann, C., Rodríguez-Pérez, R., Bajorath, J., EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph Neural Networks, ISCIENCE (2022), doi: https://doi.org/10.1016/j.isci.2022.105043
Shahini E, Pasculli G, Mastropietro A, Stolfi P, Tieri P, Vergni D, Cozzolongo R, Pesce F, Giannelli G. Network Proximity-Based Drug Repurposing Strategy for Early and Late Stages of Primary Biliary Cholangitis. Biomedicines. 2022; 10(7):1694. https://doi.org/10.3390/biomedicines10071694
2022
De Luca, R., Carfora, M., Blanco, G., Mastropietro, A., Petti, M., & Tieri, P. (2022, December). PROCONSUL: PRObabilistic exploration of CONnectivity Significance patterns for disease modULe discovery. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022 , (pp. 1941-1947). doi: 10.1109/BIBM55620.2022.9995586.
Shahini, E., Pasculli, G., Mastropietro, A., Stolfi, P., Tieri, P., Vergni, D., ... & Pesce, F. (2022). OC. 15.1 NETWORK PROXIMITY-BASED DRUG REPURPOSING STRATEGY FOR PRIMARY BILIARY CHOLANGITIS. Abstracts of the 28th National Congress of Digestive Diseases.
Also available as journal abstract as:
Shahini, E., Pasculli, G., Mastropietro, A., Stolfi, P., Tieri, P., Vergni, D., ... & Pesce, F. (2022). OC. 15.1 NETWORK PROXIMITY-BASED DRUG REPURPOSING STRATEGY FOR PRIMARY BILIARY CHOLANGITIS. Digestive and Liver Disease, 54, S106.
Marianna Maranghi, Aris Anagnostopoulos, Irene Cannistraci, Ioannis Chatzigiannakis, Federico Croce, Giulia Di Teodoro, Michele Gentile, Giorgio Grani, Maurizio Lenzerini, Stefano Leonardi, Andrea Mastropietro, Laura Palagi, Massimiliano Pappa, Riccardo Rosati, Riccardo Valentini, Paola Velardi (2022). AI-based Data Preparation and Data Analytics in Healthcare: The Case of Diabetes. Ital-IA 2022.
2019
A. Maccagno, A. Mastropietro, U. Mazziotta, M. Scarpiniti, Y.-C. Lee, A. Uncini (2019). “A CNN Approach for Audio Classification in Construction Sites,” the 29th Italian Workshop on Neural Networks (WIRN 2019), Vietri sul Mare, Salerno, Italy.
Also available as book chapter as:
A. Maccagno, A. Mastropietro, U. Mazziotta, M. Scarpiniti, Y.-C. Lee and A. Uncini, "A CNN Approach for Audio Classification in Construction Sites", in Progresses in Artificial Intelligence and Neural Systems, (A. Esposito, M. Faundez-Zanuy, F. C. Morabito and E. Pasero, Eds.), ISBN: 978-981-15-5092-8, pp. 371-381, Springer 2021.