Statistical Data Analysis

We develop computational methods and software for the analysis of primary experimental data as well as for the systematic higher-level analysis of functional relationships between genes and gene products. We are working together with various experimental groups, of which we get data for analysis. Our main aim is to develop methods that after primary statistical data analysis allow a more detailed functional analysis and understanding of the data. For this we employ gene ontology, pattern and pathway analysis. We aim to construct functional gene networks that allow intuitive visualization of data and enable Systems Biology approaches.

The division has pioneered methods (e.g. VSN) for the analysis of microarray data (Beißbarth 2000, Huber 2002), the analysis and dissemination of data from cellular assays (Hahne 2006), analysis of data from protein microarrays (Korf 2008) and has been instrumental in the setup of the leading open-source software platform Bioconductor for statistical data analysis in the life-sciences (Gentleman 2004). We have also pioneered methods for the functional interpretation of genomics data in the context of Gene Ontology and pathways (Beißbarth 2005, Fröhlich 2008).