Bioinformatics
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 part 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 involved in 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. The team developed and hosts the web-portal of the European Mouse Mutant Cell Repository (EuMMCR), the central distribution unit of mutant embryonic stem cell lines of EUCOMM (European Conditional Mouse Mutagensis Program). We are partner of 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. As a partner in the Helmholtz Alliance for Mental Health in an Ageing Society (HelMA) we 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. 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.
- Workflow of bioinformatics analysis of promoter sequences and gene expression data to identify modules of transcription factor binding sites (TFBSs).
- The data environment of the DiGtoP web portal, a resource for molecular interactions of disease-related genes (From Disease Genes To Protein Pathways)
Funding:
Our work is supported by:
Most important publications:
Augustin R, Lichtenthaler SF, Greeff M, Hansen J, Wurst W, Trümbach D (2011) Bioinformatics identification of modules of transcription factor binding sites in Alzheimer's disease-related genes by in silico promoter analysis and microarrays. Int J Alzheimers Dis. 2011 Apr 26; 2011: 154325
Ringwald M, Iyer V, Mason JC, Stone KR, Tadepally HD, Kadin JA, Bult CJ, Eppig JT, Oakley DJ, Briois S, Stupka E, Maselli V, Smedley D, Liu S, Hansen J, Baldock R, Hicks GG, Skarnes WC (2010) The IKMC web portal: a central point of entry to data and resources from the International Knockout Mouse Consortium. Nucleic Acid Res. 39, D849-D855.
Trümbach D*, Graf C*, Pütz B, Kühne C, Panhuysen M, Weber P, Holsboer F, Wurst W, Welzl G, Deussing JM (2010) Deducing corticotropin-releasing hormone receptor type 1 signaling networks from gene expression data by usage of genetic algorithms and graphical Gaussian models. BMC Systems Biology 4, 159.
Horn C*, Hansen J*, Schnütgen, F., Seisenberger, C., Floss, T., Irgang, M., De-Zolt, S., Wurst, W., von Melchner, H., Ruiz Noppinger, P. (2007) Splinkerette PCR for more efficient characterization of gene trap events. Nature Genetics 39, 933 - 934.
Hansen J, Floss T, van Sloun P, Füchtbauer EM, Arnold HH, Vauti F, Schnütgen F, Wurst W, von Melchner H, Ruiz P (2003) A large scale, gene-driven mutagenesis approach for the functional analysis of the mouse genome. Proc Nat Acad Sci (USA) 100, 9918-9922.