2011•Unpublished venueRequires access

Semantic systems biology

Erick Antezana, Ward Blondé, Aravind Venkatesan, Bernard De Baets, Vladimir Mironov, Martin T. R. Kuiper

Open publisher page 2 citations

Abstract

The vast amounts of knowledge in the biomedical domain have paved the way for a new paradigm in biological research called Systems Biology, essentially an approach that relies on the integration of all available knowledge of a biological system in a single model. This approach promotes a comprehensive understanding of biological systems, driven by data integration and mathematical modelling. However, the sheer volume, variation and complexity of the current biological data pose a number of hurdles in knowledge management that need to be overcome. The Semantic Web offers various solutions to these challenges. With our initiative, named Semantic Systems Biology (SSB), we augment the systems biology approach with semantic web technologies to enable smooth data integration, rigorous knowledge representation, efficient querying, and hypothesis generation. Here we present an overview of the projects associated with the SSB initiative. Access to our resources developed within the SSB frame is provided on our website: http://www.semantic-systems-biology.org.

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What this paper is about

The vast amounts of knowledge in the biomedical domain have paved the way for a new paradigm in biological research called Systems Biology, essentially an approach that relies on the integration of all available knowledge of a biological system in a single model. This approach promotes a comprehensive understanding of biological systems, driven by data integration and mathematical modelling. However, the sheer volume, variation and complexity of the current biological data pose a number of hurdles in knowledge management that need to be overcome. The Semantic Web offers various solutions to these challenges. With our initiative, named Semantic Systems Biology (SSB), we augment the systems biology approach with semantic web technologies to enable smooth data integration, rigorous knowledge representation, efficient querying, and hypothesis generation. Here we present an overview of the projects associated with the SSB initiative. Access to our resources developed within the SSB frame is provided on our website: http://www.semantic-systems-biology.org.

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Available abstract

The vast amounts of knowledge in the biomedical domain have paved the way for a new paradigm in biological research called Systems Biology, essentially an approach that relies on the integration of all available knowledge of a biological system in a single model. This approach promotes a comprehensive understanding of biological systems, driven by data integration and mathematical modelling. However, the sheer volume, variation and complexity of the current biological data pose a number of hurdles in knowledge management that need to be overcome. The Semantic Web offers various solutions to these challenges. With our initiative, named Semantic Systems Biology (SSB), we augment the systems biology approach with semantic web technologies to enable smooth data integration, rigorous knowledge representation, efficient querying, and hypothesis generation. Here we present an overview of the projects associated with the SSB initiative. Access to our resources developed within the SSB frame is provided on our website: http://www.semantic-systems-biology.org.

Key concepts: Computer science, Semantic Web, Systems biology, Biological data, Data science, Domain (mathematical analysis), Frame (networking), Data integration

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