The team Bioinformatics is involved in a wide variety of activities related to the development of informatic infrastructures, gene function analysis, analysis of high-throughput data, modelling of genetic and protein interaction networks, and statistical data analysis. It is a major aim of the team to provide the informatic infrastructure for large-scale genomics and proteomics projects.We develop databases and software tools for the storage of the data, for data exchange and data visualization.

The team is an integral group of the German Gene Trap Consortium (GGTC) and analysed and annotated more than 75.000 gene trap vector insertion into the genome of mouse embryonic stem cells. We are member of the International Data Coordination Center (I-DCC), a consortium that aimed at to unify the data of all mouse mutagenesis resources world-wide in a common data environment and webportal. We host the web-portal of the European Mouse Mutant Cell Repository (EuMMCR), the central distribution unit of mutant embryonic stem cell lines of EUCOMM. We are partner in the NGFN consortium DiGtoP (From Disease Genes to Protein Pathways), a project aiming to understand the complex interactions of disease-related genes/proteins.

Within this context we develop a web-based protein information portal and establish databases for sample processing and proteomics data acquired by mass spectrometry and live imaging. We further focus on the modelling of genetic interactions and extend regulatory networks by prediction of genetic interactions integrating high-throughput gene expression data and in-silico promoter analyses based on sophisticated statistical analyses.

Furthermore, we built up Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary and additional regions of the developing mouse CNS ( Genetic interaction data stored in the Mouse IDGenes database can be used for the prediction of new target genes of the Wnt and other signaling pathways (e.g. Shh, Fgf8 and BMPs) and/or for dynamic modeling approaches.

As the focus will be on neurodegenerative and neuropsychiatric diseases and their interrelationships gene expression data coming from cell lines and mice with mutations in disease-related genes is used. Recent activities are directed towards the genomewide prediction of TAL (transcription activator-like) effector nuclease cleavage sites and their visualization.

Figure 1:
Workflow of bioinformatics analysis of promoter sequences and gene expression data to identify modules of transcription factor binding sites (TFBSs)



Figure 2:
Webbased graphical visualization of predicted TAL effector nuclease binding and cleavage sites in the Otx1 gene of the mouse.