| Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, the FlowCAP Consortium, ... Nature methods, 2013 | 720 | 2013 |
| Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. MJ McConnell, JV Moran, A Abyzov, S Akbarian, T Bae, I Cortes-Ciriano, ... Science 356 (6336), eaal1641, 2017 | 285 | 2017 |
| Inferring causal molecular networks: empirical assessment through a community-based effort SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ... Nature Methods, 2016 | 284 | 2016 |
| Long-term Outcomes and Predictive Ability of Simple Non-Invasive Scoring Systems in Patients with Non-Alcoholic Fatty Liver Disease R Younes, GP Caviglia, O Govaere, C Rosso, A Armandi, T Sanavia, ... Journal of Hepatology, 2021 | 202 | 2021 |
| Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine T Sanavia, G Birolo, L Montanucci, P Turina, E Capriotti, P Fariselli Computational and structural biotechnology journal 18, 1968-1979, 2020 | 169 | 2020 |
| 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, 2022 | 151 | 2022 |
| Synaptotagmin 4 regulates pancreatic β cell maturation by modulating the Ca2+ sensitivity of insulin secretion vesicles C Huang, EM Walker, PK Dadi, R Hu, Y Xu, W Zhang, T Sanavia, J Mun, ... Developmental cell 45 (3), 347-361. e5, 2018 | 123 | 2018 |
| 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 | 69 | 2021 |
| Necroptosis-driving genes RIPK1, RIPK3 and MLKL-p are associated with intratumoral CD3+ and CD8+ T cell density and predict prognosis in hepatocellular carcinoma L Nicolè, T Sanavia, R Cappellesso, V Maffeis, J Akiba, A Kawahara, ... Journal for immunotherapy of cancer 10 (3), e004031, 2022 | 66 | 2022 |
| The need for multimodal health data modeling: A practical approach for a federated-learning healthcare platform F Cremonesi, V Planat, V Kalokyri, H Kondylakis, T Sanavia, ... Journal of biomedical informatics 141, 104338, 2023 | 59 | 2023 |
| 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, 13738, 2022 | 58 | 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 | 51 | 2021 |
| DNA methylation profiling reveals common signatures of tumorigenesis and defines epigenetic prognostic subtypes of canine Diffuse Large B-cell Lymphoma S Ferraresso, A Aricò, T Sanavia, S Da Ros, M Milan, L Cascione, ... Scientific Reports 7 (1), 11591, 2017 | 45 | 2017 |
| MiR-200c-3p contrasts PD-L1 induction by combinatorial therapies and slows proliferation of epithelial ovarian cancer through downregulation of β-catenin and c-myc E Anastasiadou, E Messina, T Sanavia, L Mundo, F Farinella, S Lazzi, ... Cells 10 (3), 519, 2021 | 43 | 2021 |
| Oncofetal gene SALL4 and prognosis in cancer: A systematic review with meta-analysis L Nicolè, T Sanavia, N Veronese, R Cappellesso, C Luchini, P Dabrilli, ... Oncotarget 2, 2b, 2017 | 43 | 2017 |
| A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis DP Noren, BL Long, R Norel, K Rrhissorrakrai, K Hess, CW Hu, ... PLOS Comput Biol 12 (6), e1004890, 2016 | 39 | 2016 |
| Serum ferritin levels can predict long-term outcomes in patients with metabolic dysfunction-associated steatotic liver disease A Armandi, T Sanavia, R Younes, GP Caviglia, C Rosso, O Govaere, ... Gut 73 (5), 825-834, 2024 | 37 | 2024 |
| Protein stability perturbation contributes to the loss of function in haploinsufficient genes G Birolo, S Benevenuta, P Fariselli, E Capriotti, E Giorgio, T Sanavia Frontiers in Molecular Biosciences 8, 10, 2021 | 37 | 2021 |
| FunPat: function-based pattern analysis on RNA-seq time series data T Sanavia, F Finotello, B Di Camillo BMC genomics 16 (Suppl 6), S2, 2015 | 37 | 2015 |
| Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment. B Di Camillo, T Sanavia, M Martini, G Jurman, F Sambo, A Barla, ... PloS one 7 (3), e32200, 2012 | 37 | 2012 |
Piero FariselliDept. of Medical Sciences, University of Torino, ItalyVerified email at unito.it
