PETRINI, ALESSANDRO
PETRINI, ALESSANDRO
Dipartimento di Informatica Giovanni Degli Antoni
Deep neural networks compression: A comparative survey and choice recommendations
2023 G.C. Marinó, A. Petrini, D. Malchiodi, M. Frasca
Automated image analysis to assess hygienic behaviour of honeybees
2022 G. Paolillo, A. Petrini, E. Casiraghi, M.G. De Iorio, S. Biffani, G. Pagnacco, G. Minozzi, G. Valentini
ParSMURF-NG: A Machine Learning High Performance Computing System for the Analysis of Imbalanced Big Omics Data
2022 A. Petrini, M. Notaro, J. Gliozzo, T. Castrignanò, P.N. Robinson, E. Casiraghi, G. Valentini
Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques
2022 L. Cappelletti, A. Petrini, J. Gliozzo, E. Casiraghi, M. Schubach, M. Kircher, G. Valentini
Heterogeneous data integration methods for patient similarity networks
2022 J. Gliozzo, M. Mesiti, M. Notaro, A. Petrini, A. Patak, A. Puertas-Gallardo, A. Paccanaro, G. Valentini, E. Casiraghi
HIGH PERFORMANCE COMPUTING MACHINE LEARNING METHODS FOR PRECISION MEDICINE
2021 A. Petrini
A bioinformatic pipeline for image analysis of varroa related traits in honeybees comb images
2021 G. Paolillo, E. Casiraghi, A. Petrini, M.G. DE IORIO, S. Biffani, G. Minozzi, A. Stella, G. Valentini
Abdominal Computed Tomography Imaging Findings in Hospitalized COVID-19 Patients: A Year-Long Experience and Associations Revealed by Explainable Artificial Intelligence
2021 A. Scarabelli, M. Zilocchi, E. Casiraghi, P. Fasani, G. Giovanni Plensich, A. Alessandro Esposito, E. Stellato, A. Petrini, J. Reese, P. Robinson, G. Valentini, G. Carrafiello
Analysis of a parallel MCMC algorithm for graph coloring with nearly uniform balancing
2021 D. Conte, G. Grossi, R. Lanzarotti, J. Lin, A. Petrini
HEMDAG: a family of modular and scalable hierarchical ensemble methods to improve Gene Ontology term prediction
2021 M. Notaro, M. Frasca, A. Petrini, J. Gliozzo, E. Casiraghi, P.N. Robinson, G. Valentini
parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants
2020 A. Petrini, M. Mesiti, M. Schubach, M. Frasca, D. Danis, M. Re, G. Grossi, L. Cappelletti, T. Castrignano, P.N. Robinson, G. Valentini
Human Digital Twin for Fitness Management
2020 B.R. Barricelli, E. Casiraghi, J. Gliozzo, A. Petrini, S. Valtolina
Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction
2020 J. Gliozzo, P. Perlasca, M. Mesiti, E. Casiraghi, V. Vallacchi, E. Vergani, M. Frasca, G. Grossi, A. Petrini, M. Re, A. Paccanaro, G. Valentini
Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions
2020 M. Frasca, M. Sepehri, A. Petrini, G. Grossi, G. Valentini
Bayesian Optimization Improves Tissue-Specific Prediction of Active Regulatory Regions with Deep Neural Networks
2020 L. Cappelletti, A. Petrini, J. Gliozzo, E. Casiraghi, M. Schubach, M. Kircher, G. Valentini
Enhanced multicore–manycore interaction in high-performance video encoding
2020 G. Grossi, P. Paglierani, F. Pedersini, A. Petrini
A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks
2020 C.T. Ba, E. Casiraghi, M. Frasca, J. Gliozzo, G. Grossi, M. Mesiti, M. Notaro, P. Perlasca, A. Petrini, M. Re', G. Valentini
Training Neural Networks with Balanced Mini-batch to Improve the Prediction of Pathogenic Genomic Variants in Mendelian Diseases
2019 L. Cappelletti, J. Gliozzo, A. Petrini, G. Valentini
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
2019 N. Zhou, Y. Jiang, T.R. Bergquist, A.J. Lee, B.Z. Kacsoh, A.W. Crocker, K.A. Lewis, G. Georghiou, H.N. Nguyen, M.N. Hamid, L. Davis, T. Dogan, V. Atalay, A.S. Rifaioglu, A. Dalklran, R. Cetin Atalay, C. Zhang, R.L. Hurto, P.L. Freddolino, Y. Zhang, P. Bhat, F. Supek, J.M. Fernandez, B. Gemovic, V.R. Perovic, R.S. Davidovic, N. Sumonja, N. Veljkovic, E. Asgari, M.R.K. Mofrad, G. Profiti, C. Savojardo, P.L. Martelli, R. Casadio, F. Boecker, H. Schoof, I. Kahanda, N. Thurlby, A.C. Mchardy, A. Renaux, R. Saidi, J. Gough, A.A. Freitas, M. Antczak, F. Fabris, M.N. Wass, J. Hou, J. Cheng, Z. Wang, A.E. Romero, A. Paccanaro, H. Yang, T. Goldberg, C. Zhao, L. Holm, P. Toronen, A.J. Medlar, E. Zosa, I. Borukhov, I. Novikov, A. Wilkins, O. Lichtarge, P.-. Chi, W.-. Tseng, M. Linial, P.W. Rose, C. Dessimoz, V. Vidulin, S. Dzeroski, I. Sillitoe, S. Das, J.G. Lees, D.T. Jones, C. Wan, D. Cozzetto, R. Fa, M. Torres, A. Warwick Vesztrocy, J.M. Rodriguez, M.L. Tress, M. Frasca, M. Notaro, G. Grossi, A. Petrini, M. Re, G. Valentini, M. Mesiti, D.B. Roche, J. Reeb, D.W. Ritchie, S. Aridhi, S.Z. Alborzi, M.-. Devignes, D.C.E. Koo, R. Bonneau, V. Gligorijevic, M. Barot, H. Fang, S. Toppo, E. Lavezzo, M. Falda, M. Berselli, S.C.E. Tosatto, M. Carraro, D. Piovesan, H. Ur Rehman, Q. Mao, S. Zhang, S. Vucetic, G.S. Black, D. Jo, E. Suh, J.B. Dayton, D.J. Larsen, A.R. Omdahl, L.J. Mcguffin, D.A. Brackenridge, P.C. Babbitt, J.M. Yunes, P. Fontana, F. Zhang, S. Zhu, R. You, Z. Zhang, S. Dai, S. Yao, W. Tian, R. Cao, C. Chandler, M. Amezola, D. Johnson, J.-. Chang, W.-. Liao, Y.-. Liu, S. Pascarelli, Y. Frank, R. Hoehndorf, M. Kulmanov, I. Boudellioua, G. Politano, S. Di Carlo, A. Benso, K. Hakala, F. Ginter, F. Mehryary, S. Kaewphan, J. Bjorne, H. Moen, M.E.E. Tolvanen, T. Salakoski, D. Kihara, A. Jain, T. Smuc, A. Altenhoff, A. Ben-Hur, B. Rost, S.E. Brenner, C.A. Orengo, C.J. Jeffery, G. Bosco, D.A. Hogan, M.J. Martin, C. O'Donovan, S.D. Mooney, C.S. Greene, P. Radivojac, I. Friedberg
A Parallel MCMC Algorithm for the Balanced Graph Coloring Problem
2019 D. Conte, G. Grossi, R. Lanzarotti, J. Lin, A. Petrini