RDFScape: Semantic Web meets systems biology.
BACKGROUND
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.


RESULTS
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.


CONCLUSIONS
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.
Splendiani
Andrea
A
UPRES-EA 3888-Laboratoire d'Informatique Médicale, Faculté de Médecine, Université Rennes 1, Rennes FR-35043, France. andrea.splendiani@univ-rennes1.fr
D000465:Algorithms; D003628:Database Management Systems; D016208:Databases, Factual; D009323:Natural Language Processing; D010506:Periodicals as Topic; D012660:Semantics; D012984:Software; D049490:Systems Biology / Q000379:methods*; D009626:Terminology as Topic