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Measurements on biological systems generate an abundance of data. These data have to be transformed to information (summarised) and presented to the user (visualised). One way of doing both simultaneously is by using models.

Our general aim is to develop and validate methods for organising, summarising and visualising complex biological data for systems biology through the integration of bioinformatics and biostatistics. 

Knowledge representation and integration is a typical bioinformatics activity. The represented knowledge can be used as a priori knowledge and combined with data-driven models using grey modelling techniques. A challenging application area is human systems biology where complex data are generated that cannot be analysed without using models.

The Top Institute for Food and Nutrition dataset is a collaborative effort of TNO, ACTA and UvA. Here, the effect of an intervention where subjects were not allowed to brush their teeth is measured using clinical, oral microbiome and metabolome data. The datasets are shown as cubes with individuals as rows, timepoints as columns and features as the third dimension. Relationships between some of the datasets have been published before, shown as green lines. Current work is on investigating the interaction between the microbiome and metabolome, shown as the blue lines. Work is also being done on identifying biomarkers (red line) important to the oral microbiome and metabolome response to the intervention.