Background: Life scientists need help in coping with the plethora of fast growing and scatteredknowledge resources. Ideally, this knowledge should be integrated in a form that allows them topose complex questions that address the properties of biological systems, independently from theorigin of the knowledge. Semantic Web technologies prove to be well suited for knowledgeintegration, knowledge production (hypothesis formulation), knowledge querying and knowledgemaintenance.Results: We implemented a semantically integrated resource named BioGateway, comprising theentire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROTprotein set, the NCBI taxonomy and several in-house ontologies. BioGateway provides a singleentry point to query these resources through SPARQL. It constitutes a key component for aSemantic Systems Biology approach to generate new hypotheses concerning systems properties. Inthe course of developing BioGateway, we faced challenges that are common to other projects thatinvolve large datasets in diverse representations. We present a detailed analysis of the obstaclesthat had to be overcome in creating BioGateway. We demonstrate the potential of acomprehensive application of Semantic Web technologies to global biomedical data.Conclusion: The time is ripe for launching a community effort aimed at a wider acceptance andapplication of Semantic Web technologies in the life sciences. We call for the creation of a forumthat strives to implement a truly semantic life science foundation for Semantic Systems Biology.
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