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This article is part of the supplement: A Semantic Web for Bioinformatics: Goals, Tools, Systems, Applications

Open Access Research

RDFScape: Semantic Web meets Systems Biology

Andrea Splendiani

Author Affiliations

UPRES-EA 3888 - Laboratoire d'Informatique Médicale, Faculté de Médecine, Université Rennes 1, Rennes FR-35043, France

Unité de Biologie Systemique, Institut Pasteur, Paris FR-75015, France

BMC Bioinformatics 2008, 9(Suppl 4):S6  doi:10.1186/1471-2105-9-S4-S6

Published: 25 April 2008



The recent availability of high-throughput data in molecular biology has increased the need for a formal representation of this knowledge domain. New ontologies are being developed to formalize knowledge, e.g. about the functions of proteins. As the Semantic Web is being introduced into the Life Sciences, the basis for a distributed knowledge-base that can foster biological data analysis is laid. However, there still is a dichotomy, in tools and methodologies, between the use of ontologies in biological investigation, that is, in relation to experimental observations, and their use as a knowledge-base.


RDFScape is a plugin that has been developed to extend a software oriented to biological analysis with support for reasoning on ontologies in the semantic web framework. We show with this plugin how the use of ontological knowledge in biological analysis can be extended through the use of inference. In particular, we present two examples relative to ontologies representing biological pathways: we demonstrate how these can be abstracted and visualized as interaction networks, and how reasoning on causal dependencies within elements of pathways can be implemented.


The use of ontologies for the interpretation of high-throughput biological data can be improved through the use of inference. This allows the use of ontologies not only as annotations, but as a knowledge-base from which new information relevant for specific analysis can be derived.