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This article is part of the supplement: Semantic Web Applications and Tools for Life Sciences, 2008

Open Access Research

BioGateway: a semantic systems biology tool for the life sciences

Erick Antezana12, Ward Blondé3, Mikel Egaña4, Alistair Rutherford5, Robert Stevens4, Bernard De Baets3, Vladimir Mironov6 and Martin Kuiper6*

Author Affiliations

1 Dept of Plant Systems Biology, VIB, Gent, Belgium

2 Dept of Molecular Genetics, Ghent University, Belgium

3 Dept of Applied Mathematics, Biometrics and Process Control, Ghent University, Belgium

4 School of Computer Science, University of Manchester, UK

5, Glasgow, UK

6 Dept. of Biology, Norwegian University of Science and Technology, Trondheim, Norway

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BMC Bioinformatics 2009, 10(Suppl 10):S11  doi:10.1186/1471-2105-10-S10-S11

Published: 1 October 2009



Life scientists need help in coping with the plethora of fast growing and scattered knowledge resources. Ideally, this knowledge should be integrated in a form that allows them to pose complex questions that address the properties of biological systems, independently from the origin of the knowledge. Semantic Web technologies prove to be well suited for knowledge integration, knowledge production (hypothesis formulation), knowledge querying and knowledge maintenance.


We implemented a semantically integrated resource named BioGateway, comprising the entire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROT protein set, the NCBI taxonomy and several in-house ontologies. BioGateway provides a single entry point to query these resources through SPARQL. It constitutes a key component for a Semantic Systems Biology approach to generate new hypotheses concerning systems properties. In the course of developing BioGateway, we faced challenges that are common to other projects that involve large datasets in diverse representations. We present a detailed analysis of the obstacles that had to be overcome in creating BioGateway. We demonstrate the potential of a comprehensive application of Semantic Web technologies to global biomedical data.


The time is ripe for launching a community effort aimed at a wider acceptance and application of Semantic Web technologies in the life sciences. We call for the creation of a forum that strives to implement a truly semantic life science foundation for Semantic Systems Biology.

Access to the system and supplementary information (such as a listing of the data sources in RDF, and sample queries) can be found at webcite.