The Semantic Web for Complex Network Analysis in Biomedical Domain

Complex networks of direct relevance to biomedicine have not yet been fully mapped largely due to the incompleteness, isolation, and heterogeneity of data. The Semantic Web, by providing a technical framework for the integration and sharing of heterogeneous databases in different domains, can potentially enable more effective complex network mapping and analysis. However, the feasibility of using the Semantic Web for biomedical complex network analysis should be further investigated. In this paper, we propose the semantic graph mining methodology that uses the semantic graph model to integrate graph mining and ontology reasoning for better analyzing biomedical complex networks. We also present reference architecture and a set of recommended biomedical use cases in order to implement this methodology.