  In biomedical research, unified access to up-to-date domain-specific
knowledge is crucial, as such knowledge is continuously accumulated in
scientific literature and structured resources. Identifying and extracting
specific information is a challenging task and computational analysis of
knowledge bases can be valuable in this direction. However, for
disease-specific analyses researchers often need to compile their own datasets,
integrating knowledge from different resources, or reuse existing datasets,
that can be out-of-date. In this study, we propose a framework to automatically
retrieve and integrate disease-specific knowledge into an up-to-date semantic
graph, the iASiS Open Data Graph. This disease-specific semantic graph provides
access to knowledge relevant to specific concepts and their individual aspects,
in the form of concept relations and attributes. The proposed approach is
implemented as an open-source framework and applied to three diseases (Lung
Cancer, Dementia, and Duchenne Muscular Dystrophy). Exemplary queries are
presented, investigating the potential of this automatically generated semantic
graph as a basis for retrieval and analysis of disease-specific knowledge.
