Responsible: Prof. Edgar Wingender, University of Goettingen.

Background:

The integration of clinical and classical ‘omics’ data promises novel insights into the molecular basis of pathological phenotypes. With this comes the promise of rationally designed diagnostic and therapeutic intervention procedures. The research activities of this particular sub-project will focus on the integration of disease aberration information into metabolic, signal-transduction and genetic networks. In so doing, we also intend to perform network reconstructions from experimental data (e.g. microarray analyses), compare the networks of healthy and diseased states, assist in data interpretation regarding the molecular etiology of disease, as well as validate target genes and computer-assisted therapeutic molecule discovery.

Planned work:

a) Ontology-based data integration – We intend to develop an ontology that will facilitate us in integrating disparate databases of biomolecular network information and their components.

b) Network reconstruction – We intend to reconstruct differential views on single networks pertaining to the healthy and diseased states, primarily using gene expression data. The analysis of the promoter regions and the associated reconstruction of the upstream sub-networks will also be addressed.

c) Automatic network annotation - Methods for the natural-language based analysis of medical texts will be developed, with a particular emphasis on the extraction of medically relevant dys-regulation information.

d) Network comparison – Graph based methods will be developed to facilitate the identification of critical differences between wild-type and pathologically aberrant networks.