Gaining control of the oscillation of biological pathways may provide new possibilities to influence biological processes like inflammation. Hence, we will search (assisted by the models and databases developed) for small molecules interfering with the NF-kappaB oscillation and validate selected candidates in experimental systems. Owing to its highly focused system biological approach, the project will generate substantial insights into key mechanisms underlying IBD.

GeneXplain will be involved in the dynamic simulation of the oscillating processed described above, and in the identification of suitable targets and drug candidates, which will then be experimentally validated by the partners.

It was triggered by the repeated observation that the existing methodology for analyzing huge data sets does not match by far the complexity of the biological problem addressed. Expensive and complex data are gathered and being analysed in a rather simple way, thereby missing the opportunity to uncover combinations of predictive and meaningful profiles among the different kinds of omics data. Novel methods should integrate multilevel omics data to bring biological understanding to the next level. Due to the high dimensionality of the datasets the multiple testing burden becomes heavier and consequently the false positive and negative rates increase. Super-meta methods combining multilevel data across populations need to be developed.

GeneXPlain will provide the consortium with the geneXplain platform for data handling and analysis in order to integrate databases of molecular networks with state of the art bioinformatics and systems biology tools. This way, we will support the analysis of pre-existing omics data and apply them for building efficient systems biology models. We will also work on integrating analytical tools developed within the MIMOmics project with already existing systems biology data and knowledge. GeneXplain will be strongly involved in the project’s dissemination activities, thereby particularly considering potential partners from industries.

• build a computational model for analyzing the kinetics of plasma lipids, lipoproteins and their interactions with glucose metabolism;
• apply the iterative systems biology cycle for calibrating, validating and improving the computational model in dedicated studies in mice;

• build, calibrate and validate the computational model for use in humans;
• analyze – based on model and experimental data – which processes in the murine metabolic network regulatethe physiological response to perturbations in lipid, lipoprotein and glucose metabolism and how these interact;
• analyze – based on model and experimental data – which processes in the human metabolic network regulatethe physiological response to perturbations in lipid, lipoprotein and glucose metabolism and how these interact;
• use the human model to identify network-based drug targets aimed at restoring the metabolic dyslipidemia and glycemic control in patients with MetS and associated comorbidities.

The 60-months project RESOLVE will result into a novel strategy for development of therapeutic strategies for MetS patients with T2DM, NAFLD or CVD.