Work Package 4 - WP4

Effective coordination between the experimental, bioinformatics and modeling tasks is pivotal for the success of an interdisciplinary project and the outlined systems medicine approach. The multiple and heterogeneous data sets from WP1, 2, 3, 5 and 6 are aggregated in a dynamic, relational database.
Multivariate statistics, machine learning and reverse engineering approaches will allow pinpointing and mapping key nodes and biomarkers from heterogeneous (meta-)data both from the tested pathogens and the murine and human hosts. These top-down analyses are iteratively combined with bottom-up modeling of specific sub-networks/biomarker sets previously identified in both the pathogens and host as being important for the onset of NTSI. Using the time-dependent profiles of relevant cytokine/chemokines as well as other accessory compounds generated, we build simplified dynamic models describing key cellular and cytokine network interactions. Validation will be done in WP3, 4, 5 and 6 guided by model-driven experimental design. The initial model will be a scaffold on which to add other cells, cytokines, and interactions, as new data warrant. This iterative procedure and modeling framework will lead to refined hypotheses on biomarker sets, key networks involved and of their dynamics, and role in disease. Special attention will be given to the heterogeneity of these infections, which is important to address in order to understand the disease.