Data and knowledge integration methods for network systems biology

Client ID: ARRS (J2-2197)
Project type: Basic Research and Application Project
Project duration: 2009 - 2012

Research in biomedicine is being revolutionized by new experimental technologies, information infrastructures and emerging data encoding standards for storage of results and knowledge in various databases, ontologies, textual descriptions and tagged libraries. New methods for explorative analysis that preserve the contextual and structural richness of these information sources and support the daily work of biologists by exposing the most important relations in a visually rich, comprehensive, and easy-to-use interface.

In the project we will develop and apply a set of integrative computational and visualization tools for inference of hypotheses from heterogeneous data and knowledge sources. These will be applied to the reconstruction of adiponectin signalling pathway, an emerging drug target for obesity and type 2 diabetes, and in the study of side effects of statins and their role in cholesterol pathways. With current practical demonstrations in this field being rare and focusing only on a single source of information, the development and application of data/knowledge integration techniques should be regarded as highly original.