about
Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational modelsComputational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome.Variability in tuberculosis granuloma T cell responses exists, but a balance of pro- and anti-inflammatory cytokines is associated with sterilizationDifferences in reactivation of tuberculosis induced from anti-TNF treatments are based on bioavailability in granulomatous tissueMacrophage polarization drives granuloma outcome during Mycobacterium tuberculosis infectionMultiscale computational modeling reveals a critical role for TNF-α receptor 1 dynamics in tuberculosis granuloma formation.An automated procedure for the extraction of metabolic network information from time series data.Intracellular bacillary burden reflects a burst size for Mycobacterium tuberculosis in vivo.Tumor necrosis factor blockade in chronic murine tuberculosis enhances granulomatous inflammation and disorganizes granulomas in the lungsMathematical modeling of primary succession of murine intestinal microbiota.An anthropologically based model of the impact of asymptomatic cases on the spread of Neisseria gonorrhoeae.Mycobacterium tuberculosis as viewed through a computer.A hybrid multi-compartment model of granuloma formation and T cell priming in tuberculosis.Microenvironments in tuberculous granulomas are delineated by distinct populations of macrophage subsets and expression of nitric oxide synthase and arginase isoforms.A methodology for performing global uncertainty and sensitivity analysis in systems biology.A multifaceted approach to modeling the immune response in tuberculosis.Computational modeling predicts IL-10 control of lesion sterilization by balancing early host immunity-mediated antimicrobial responses with caseation during mycobacterium tuberculosis infectionPhase variation and host immunity against high molecular weight (HMW) adhesins shape population dynamics of nontypeable Haemophilus influenzae within human hosts.Dendritic cell trafficking and antigen presentation in the human immune response to Mycobacterium tuberculosis.The human immune response to Mycobacterium tuberculosis in lung and lymph node.Regulation of glycolysis in Lactococcus lactis: an unfinished systems biological case study.Computing DIT from energy expenditure measures in a respiratory chamber: a direct modeling method.HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasetsPredictive Big Data Analytics using the UK Biobank DataDifferent limit to the body's ability of increasing fat-free massDynamic balance of pro- and anti-inflammatory signals controls disease and limits pathologyA review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment
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description
researcher ORCID ID = 0000-0002-0051-8198
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wetenschapper
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name
Simeone Marino
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Simeone Marino
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Simeone Marino
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Simeone Marino
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type
label
Simeone Marino
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Simeone Marino
@en
Simeone Marino
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Simeone Marino
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prefLabel
Simeone Marino
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Simeone Marino
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Simeone Marino
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Simeone Marino
@nl
P106
P1153
8786377400
P31
P496
0000-0002-0051-8198