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BioGateway: A Semantic Systems Biology Tool for the Life Sciences

Antezana, Erick; Blondé, Ward; Egaña, Mikel; Rutherford, Alistair; Stevens, Robert; De baets, Bernard; Mironov, Vladimir; Kuiper, Martin
Journal article, Peer reviewed
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1471-2105-10-S10-S11.pdf (426.8Kb)
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http://hdl.handle.net/11250/2384279
Utgivelsesdato
2009
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  • Institutt for biologi [2004]
  • Publikasjoner fra CRIStin - NTNU [26746]
Originalversjon
BMC Bioinformatics 2009, 10(S11)   10.1186/1471-2105-10-S10-S11
Sammendrag
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.
Utgiver
BioMed Central
Tidsskrift
BMC Bioinformatics

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