BioGateway: a semantic systems biology tool for the life sciences

doi:10.1186/1471-2105-10-S10-S11

BMC Bioinformatics
Volume 10
Suppl 10

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Antezana E
Blondé W
Egaña M
Rutherford A
Stevens R
De Baets B
Mironov V
Kuiper M

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Antezana E
Blondé W
Egaña M
Rutherford A
Stevens R
De Baets B
Mironov V
Kuiper M
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This article is part of the supplement: Semantic Web Applications and Tools for Life Sciences, 2008 .

Research

BioGateway: a semantic systems biology tool for the life sciences

Erick Antezana¹^,2 , Ward Blondé³ , Mikel Egaña⁴ , Alistair Rutherford⁵ , Robert Stevens⁴ , Bernard De Baets³ , Vladimir Mironov⁶ and Martin Kuiper⁶

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

²Dept of Molecular Genetics, Ghent University, Belgium

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

⁴School of Computer Science, University of Manchester, UK

⁵http://www.netthreads.co.uk, Glasgow, UK

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

author email corresponding author email

BMC Bioinformatics 2009, 10(Suppl 10):S11doi:10.1186/1471-2105-10-S10-S11


Published:	1 October 2009

Abstract

Background

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.

Results

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.

Conclusion

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 http://www.semantic-systems-biology.org/biogateway webcite.