| Mutational signatures and heterogeneous host response revealed via large-scale characterization of SARS-CoV-2 genomic diversity A Graudenzi, D Maspero, F Angaroni, R Piazza, D Ramazzotti Iscience 24 (2), 2021 | 70 | 2021 |
| A review of computational strategies for denoising and imputation of single-cell transcriptomic data L Patruno, D Maspero, F Craighero, F Angaroni, M Antoniotti, A Graudenzi Briefings in bioinformatics 22 (4), bbaa222, 2021 | 50 | 2021 |
| VERSO: a comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples D Ramazzotti, F Angaroni, D Maspero, C Gambacorti-Passerini, ... Patterns 2 (3), 2021 | 27 | 2021 |
| Large-scale analysis of SARS-CoV-2 synonymous mutations reveals the adaptation to the human codon usage during the virus evolution D Ramazzotti, F Angaroni, D Maspero, M Mauri, D D’Aliberti, D Fontana, ... Virus evolution 8 (1), veac026, 2022 | 19 | 2022 |
| An optimal control framework for the automated design of personalized cancer treatments F Angaroni, A Graudenzi, M Rossignolo, D Maspero, T Calarco, R Piazza, ... Frontiers in Bioengineering and Biotechnology 8, 523, 2020 | 19 | 2020 |
| Amplification of the parametric dynamical Casimir effect via optimal control F Hoeb, F Angaroni, J Zoller, T Calarco, G Strini, S Montangero, G Benenti Physical Review A 96 (3), 033851, 2017 | 19 | 2017 |
| LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data D Ramazzotti, F Angaroni, D Maspero, G Ascolani, I Castiglioni, R Piazza, ... Journal of Computational Science 58, 101523, 2022 | 16 | 2022 |
| Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines D Ramazzotti, F Angaroni, D Maspero, G Ascolani, I Castiglioni, R Piazza, ... Nature communications 13 (1), 2718, 2022 | 13 | 2022 |
| PMCE: efficient inference of expressive models of cancer evolution with high prognostic power F Angaroni, K Chen, C Damiani, G Caravagna, A Graudenzi, ... Bioinformatics 38 (3), 754-762, 2022 | 13 | 2022 |
| Characterization of intra-host SARS-CoV-2 variants improves phylogenomic reconstruction and may reveal functionally convergent mutations D Ramazzotti, F Angaroni, D Maspero, C Gambacorti-Passerini, ... | 13 | 2020 |
| Longitudinal cancer evolution from single cells D Ramazzotti, F Angaroni, D Maspero, G Ascolani, I Castiglioni, R Piazza, ... bioRxiv, 2020.01. 14.906453, 2020 | 11 | 2020 |
| Unity is strength: Improving the detection of adversarial examples with ensemble approaches F Craighero, F Angaroni, F Stella, C Damiani, M Antoniotti, A Graudenzi Neurocomputing 554, 126576, 2023 | 10 | 2023 |
| gDNA qPCR is statistically more reliable than mRNA analysis in detecting leukemic cells to monitor CML A Rainero, F Angaroni, F D’Avila, A Conti, C Pirrone, G Micheloni, ... Cell death & disease 9 (3), 349, 2018 | 10 | 2018 |
| Applications of Picard and Magnus expansions to the Rabi model F Angaroni, G Benenti, G Strini The European Physical Journal D 72, 1-9, 2018 | 8 | 2018 |
| J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments F Angaroni, A Guidi, G Ascolani, A d’Onofrio, M Antoniotti, A Graudenzi BMC bioinformatics 23 (1), 269, 2022 | 7 | 2022 |
| Reconstruction of electromagnetic field states by a probe qubit F Angaroni, G Benenti, G Strini The European Physical Journal D 70, 1-8, 2016 | 6 | 2016 |
| Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients D Fontana, I Crespiatico, V Crippa, F Malighetti, M Villa, F Angaroni, ... Nature Communications 14 (1), 5982, 2023 | 5 | 2023 |
| On the Use of Topological Features of Metabolic Networks for the Classification of Cancer Samples J Machicao, F Craighero, D Maspero, F Angaroni, C Damiani, ... Current Genomics 22 (2), 88-97, 2021 | 5 | 2021 |
| Quantification of intra-host genomic diversity of sars-cov-2 allows a high-resolution characterization of viral evolution and reveals functionally convergent variants D Ramazzotti, F Angaroni, D Maspero, C Gambacorti-Passerini, ... BioRxiv, 2020.04. 22.044404, 2020 | 4 | 2020 |
| Investigating the compositional structure of deep neural networks F Craighero, F Angaroni, A Graudenzi, F Stella, M Antoniotti Machine Learning, Optimization, and Data Science: 6th International …, 2020 | 4 | 2020 |
