Changes in cells while they are undergoing transformation from "normal" to malignant cells (e.g. during infections) happen on many biological levels, such as genome, transcriptome, proteome and metabolome. Following the central dogma of molecular biology and its extensions these levels are highly interconnected and depend on each other. Within the MedLab, one of four labs of the Research Campus MODAL at ZIB, we will develop new mathematical methods that allow (1) identification of multivariate disease signatures that describe changes in multiple data-sources and (2) development of multi-level models that embeds these findings into the actual biological context. Both parts combined will eventually lead to a thorough understanding of the modeled process and open up the opportunity to use the respective model for diagnostic purposes for individuals, thus allowing high-throughput classification of biological samples. These techniques can then be adjusted to an individual by using its -omics data and thus allows to derive information about the individual's state, for example, as a diagnostic tool for a certain disease that is captured by the data and the model. All algorithms will be implemented using state-of-the art software frameworks that can copy with the very large data volumes.