| PI3K-driven HER2 expression is a potential therapeutic target in colorectal cancer stem cells LR Mangiapane, A Nicotra, A Turdo, M Gaggianesi, P Bianca, S Di Franco, ... Gut 71 (1), 119-128, 2022 | 64 | 2022 |
| Adipose stem cell niche reprograms the colorectal cancer stem cell metastatic machinery S Di Franco, P Bianca, DS Sardina, A Turdo, M Gaggianesi, V Veschi, ... Nature communications 12 (1), 5006, 2021 | 57 | 2021 |
| A novel computational method for inferring competing endogenous interactions DS Sardina, S Alaimo, A Ferro, A Pulvirenti, R Giugno Briefings in Bioinformatics, 2016 | 53 | 2016 |
| PNPLA3 and TLL-1 polymorphisms as potential predictors of disease severity in patients with COVID-19 S Grimaudo, E Amodio, RM Pipitone, CM Maida, S Pizzo, T Prestileo, ... Frontiers in Cell and Developmental Biology 9, 627914, 2021 | 34 | 2021 |
| Choline PET/CT features to predict survival outcome in high-risk prostate cancer restaging: a preliminary machine-learning radiomics study. P Alongi, R Laudicella, A Stefano, F Caobelli, A Comelli, A Vento, ... The quarterly journal of nuclear medicine and molecular imaging: official …, 2020 | 28 | 2020 |
| Targeting chemoresistant colorectal cancer via systemic administration of a BMP7 variant V Veschi, LR Mangiapane, A Nicotra, S Di Franco, E Scavo, T Apuzzo, ... Oncogene 39 (5), 987-1003, 2020 | 26 | 2020 |
| 18F‐Florbetaben PET/CT to Assess Alzheimer's Disease: A new Analysis Method for Regional Amyloid Quantification P Alongi, DS Sardina, R Coppola, S Scalisi, V Puglisi, A Arnone, ... Journal of Neuroimaging 29 (3), 383-393, 2019 | 24 | 2019 |
| KUALA: A machine learning-driven framework for kinase inhibitors repositioning G De Simone, DS Sardina, MR Gulotta, U Perricone Scientific Reports 12 (1), 17877, 2022 | 5 | 2022 |
| Exploring machine learning techniques to predict the response to omalizumab in chronic spontaneous urticaria DS Sardina, G Valenti, F Papia, CG Uasuf Diagnostics 11 (11), 2150, 2021 | 3 | 2021 |
| Adipose stem cell niche reprograms the colorectal cancer stem cell metastatic machinery SD Franco, P Bianca, DS Sardina, A Turdo, M Gaggianesi, V Veschi, ... Nature Communications 12 (1), 1-16, 2021 | 2 | 2021 |
| INBIA: a boosting methodology for proteomic network inference DS Sardina, G Micale, A Ferro, A Pulvirenti, R Giugno BMC bioinformatics 19 (7), 188, 2018 | 2 | 2018 |
| Correlation between proteomic network inference and protein-protein interaction networks DS Sardina, G Micale, A Ferro, A Pulvirenti, R Giugno Proc. 13th International Conferenceon on Computational Intelligence Methods …, 2016 | 2 | 2016 |
| APDB: a database on air pollutant characterization and similarity prediction E Viesi, DS Sardina, U Perricone, R Giugno Database 2023, baad046, 2023 | 1 | 2023 |
| 79. Amyloid-PET analysis based on tissue probability maps G Russo, DS Sardina, P Alongi, R Coppola, V Puglisi, A Stefano, ... Physica Medica: European Journal of Medical Physics 56, 111-112, 2018 | 1 | 2018 |
| Diagnostic Accuracy of Specific IgE to Lipid Transfer Proteins (LTPs) in Food Allergy: A Systematic Review C Bellia, DS Sardina, C Scazzone, D Lio, L Scola, CG Uasuf Preprints, 2024 | | 2024 |
| Exploring machine learning techniques to predict the response to omalizumab in chronic idiopathic urticaria DS Sardina, F Papia, G Valenti, CG Uasuf ALLERGY 76, 217-218, 2021 | | 2021 |
| Exploring Machine Learning Techniques to Predict the Response to Omalizumab in Chronic Spontaneous Urticaria. Diagnostics 2021, 11, 2150 DS Sardina, G Valenti, F Papia, CG Uasuf s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021 | | 2021 |
| PNPLA3 and TLL-1 polymorphisms affect disease severity in patients with COVID-19 S Grimaudo, E Amodio, RM Pipitone, CM Maida, S Pizzo, T Prestileo, ... | | 2020 |
| P1. 01-59 Expanding Access to Large-Scale Genomic Mutational Analyses for Patients with Advanced NSCLC in Italy V Gregorc, C Lazzari, A Guida, G Bucci, P Graziano, MG Cangi, G Frigè, ... Journal of Thoracic Oncology 14 (10), S381, 2019 | | 2019 |
| SPM MRI-less 18F-Florbetaben PET for amyloid burden quantification and potential AD patients selection in clinical trials P Alongi, R Laudicella, D Sardina, S Giliberto, G Russo, A Stefano, ... EANM'19, 2019 | | 2019 |
Giugno RosalbaProfessor University of Verona在 univr.it 的电子邮件经过验证
