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.