| Response rescaling in bacterial chemotaxis MD Lazova, T Ahmed, D Bellomo, R Stocker, TS Shimizu Proceedings of the National Academy of Sciences 108 (33), 13870-13875, 2011 | 176 | 2011 |
| Model combining tumor molecular and clinicopathologic risk factors predicts sentinel lymph node metastasis in primary cutaneous melanoma D Bellomo, SM Arias-Mejias, C Ramana, JB Heim, E Quattrocchi, ... JCO precision oncology 4, 319-334, 2020 | 77 | 2020 |
| Role of phosphate in the central metabolism of two lactic acid bacteria—a comparative systems biology approach J Levering, MWJM Musters, M Bekker, D Bellomo, T Fiedler, WM de Vos, ... FEBS Journal, 2012 | 69 | 2012 |
| Adaptive fuzzy control of a non-linear servo-drive: theory and experimental results D Bellomo, D Naso, R Babuška Engineering Applications of Artificial Intelligence 21 (6), 846-857, 2008 | 56 | 2008 |
| Identification of stage I/IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model AMM Eggermont, D Bellomo, SM Arias-Mejias, E Quattrocchi, ... European Journal of Cancer 140, 11-18, 2020 | 38 | 2020 |
| Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation E Murabito, M Verma, M Bekker, D Bellomo, HV Westerhoff, B Teusink, ... PLoS One 9 (9), e106453, 2014 | 36 | 2014 |
| Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering F Menolascina, D Bellomo, T Maiwald, V Bevilacqua, C Ciminelli, ... BMC bioinformatics 10, 1-13, 2009 | 33 | 2009 |
| Composite adaptive fuzzy control D Bellomo, D Naso, B Turchiano, R Babuška Proceedings of the 16th IFAC World Congress, Prague, Czech Republic, 2005 | 25 | 2005 |
| Stability from structure: metabolic networks are unlike other biological networks P van Nes, D Bellomo, MJT Reinders, D de Ridder EURASIP Journal on Bioinformatics and Systems Biology 2009, 1-15, 2008 | 8 | 2008 |
| Improving genetic algorithms: an approach based on multi-elitism and Lamarckian mutation D Bellomo, D Naso, B Turchiano IEEE International Conference on Systems, Man and Cybernetics 4, 6 pp. vol. 4, 2002 | 8 | 2002 |
| Ambiguous definitions for baseline serum creatinine affect acute kidney diagnosis at the emergency department M Niemantsverdriet, M Khairoun, A El Idrissi, R Koopsen, I Hoefer, ... BMC nephrology 22, 1-10, 2021 | 5 | 2021 |
| Clinicopathologic models predicting non‐sentinel lymph node metastasis in cutaneous melanoma patients: Are they useful for patients with a single positive sentinel node? B Rentroia‐Pacheco, FJ Tjien‐Fooh, E Quattrocchi, A Kobic, R Wever, ... Journal of Surgical Oncology, 2021 | 5 | 2021 |
| Identification of stage IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model. R Wever, F Tjien-Fooh, D Bellomo, E Quattrocchi, S Sominidi Damodaran, ... Journal of Clinical Oncology 38 (15_suppl), e22088-e22088, 2020 | 4 | 2020 |
| Parameter convergence in adaptive fuzzy control D Bellomo, D Naso, R Babuška First International Conference on Informatics in Control, Automation and …, 2004 | 3 | 2004 |
| Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model B Rentroia-Pacheco, S Tokez, EM Bramer, ZC Venables, ... EClinicalMedicine 63, 2023 | 2 | 2023 |
| Design, validation and implementation of an automated e-alert for acute kidney injury: 6-month pilot study shows increased awareness MSA Niemantsverdriet, WM Tiel Groenestege, M Khairoun, IE Hoefer, ... BMC nephrology 24 (1), 222, 2023 | 2 | 2023 |
| The letter responds to comment on Identification of stage I/IIA melanoma patients at high risk of disease relapse using a clinicopathologic and gene expression model AMM Eggermont, D Bellomo, J Dwarkasing, L Meerstein-Kessel, A Meves European Journal of Cancer 157, 518-519, 2021 | 2 | 2021 |
| Reply to EK Bartlett et al and AHR Varey et al D Bellomo, AG Bridges, TJ Hieken, A Meves JCO precision oncology 4, 2020 | 2 | 2020 |
| Identifying the regulatory structure of metabolic networks: a constrained optimization approach D Bellomo, D de Ridder, S Rossell, PJT Verheijen, MJT Reinders, ... Proceedings of the Fourteenth Annual Conference of the Advanced School for …, 2008 | 2 | 2008 |
| A machine learning approach using endpoint adjudication committee labels for the identification of sepsis predictors at the emergency department MSA Niemantsverdriet, TAP de Hond, IE Hoefer, WW van Solinge, ... BMC Emergency Medicine 22 (1), 208, 2022 | 1 | 2022 |
Alexander MevesAssociate Professor of Dermatology, Mayo ClinicEmail verificata su mayo.edu
