Simeone Marino
Affiliations: | 2004-2005 | BME | Georgia Institute of Technology, Atlanta, GA |
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"Simeone Marino"
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| Marino S, Zhao Y, Zhou N, et al. (2020) Compressive Big Data Analytics: An ensemble meta-algorithm for high-dimensional multisource datasets. Plos One. 15: e0228520 |
| Marino S, Hult C, Wolberg P, et al. (2018) The Role of Dimensionality in Understanding Granuloma Formation. Computation (Basel, Switzerland). 6 |
| Marino S, Zhou N, Zhao Y, et al. (2018) HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets. Journal of Statistical Computation and Simulation. 89: 249-271 |
| Marino S, Xu J, Zhao Y, et al. (2018) Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies. Plos One. 13: e0202674 |
| Cicchese JM, Evans S, Hult C, et al. (2018) Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology. Immunological Reviews. 285: 147-167 |
| Magombedze G, Marino S. (2018) Mathematical and computational approaches in understanding the immunobiology of granulomatous diseases Current Opinion in Systems Biology. 12: 1-11 |
| Kirschner D, Pienaar E, Marino S, et al. (2017) A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment. Current Opinion in Systems Biology. 3: 170-185 |
| Marino S, Kirschner DE. (2016) A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection. Computation (Basel, Switzerland). 4 |
| Marino S, Gideon HP, Gong C, et al. (2016) Computational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome. Plos Computational Biology. 12: e1004804 |
| Hazel A, Marino S, Simon C. (2015) An anthropologically based model of the impact of asymptomatic cases on the spread of Neisseria gonorrhoeae. Journal of the Royal Society, Interface / the Royal Society. 12 |