| Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset C Pancotti, S Benevenuta, G Birolo, V Alberini, V Repetto, T Sanavia, ... Briefings in Bioinformatics 23 (2), bbab555, 2022 | 25 | 2022 |
| An antisymmetric neural network to predict free energy changes in protein variants S Benevenuta, C Pancotti, P Fariselli, G Birolo, T Sanavia Journal of Physics D: Applied Physics 54 (24), 245403, 2021 | 21 | 2021 |
| DDGun: an untrained predictor of protein stability changes upon amino acid variants L Montanucci, E Capriotti, G Birolo, S Benevenuta, C Pancotti, D Lal, ... Nucleic Acids Research 50 (W1), W222-W227, 2022 | 13 | 2022 |
| A deep-learning sequence-based method to predict protein stability changes upon genetic variations C Pancotti, S Benevenuta, V Repetto, G Birolo, E Capriotti, T Sanavia, ... Genes 12 (6), 911, 2021 | 6 | 2021 |
| Deep learning methods to predict amyotrophic lateral sclerosis disease progression C Pancotti, G Birolo, C Rollo, T Sanavia, B Di Camillo, U Manera, A Chiò, ... Scientific Reports 12 (1), 13738, 2022 | 5 | 2022 |
| Multi-event survival prediction for amyotrophic lateral sclerosis C Pancotti, G Birolo, T Sanavia, C Rollo, P Fariselli CEUR WORKSHOP PROCEEDINGS 3180, 1269-1276, 2022 | 1 | 2022 |
| Unravelling the instability of mutational signatures extraction via archetypal analysis C Pancotti, C Rollo, G Birolo, S Benevenuta, P Fariselli, T Sanavia Frontiers in Genetics 13, 3618, 2023 | | 2023 |
| 1149 MACHINE-LEARNING BASED PREDICTION OF IN-HOSPITAL DEATH FOR PATIENTS WITH TAKOTSUBO SYNDROME: THE INTERTAK-ML MODEL O De Filippo, C Pancotti, VL Camman, M Bianco, S Gili, C Di Mario, ... European Heart Journal Supplements 24 (Supplement_K), suac121. 714, 2022 | | 2022 |
| Supplementary Materials for “Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset” C Pancotti, S Benevenuta, G Birolo, V Repetto, V Alberini, T Sanavia, ... | | |
| Unfederated Learning: A Framework for Survival Analysis with Data Distributed Across Multiple Institutions C Rollo, C Pancotti, G Birolo, I Rossi, T Sanavia, P Fariselli Available at SSRN 4257667, 0 | | |
Piero FariselliDept. of Medical Sciences, University of Torino, ItalyBestätigte E-Mail-Adresse bei unito.it
