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      The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery

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          Abstract

          The Semanticscience Integrated Ontology (SIO) is an ontology to facilitate biomedical knowledge discovery. SIO features a simple upper level comprised of essential types and relations for the rich description of arbitrary (real, hypothesized, virtual, fictional) objects, processes and their attributes. SIO specifies simple design patterns to describe and associate qualities, capabilities, functions, quantities, and informational entities including textual, geometrical, and mathematical entities, and provides specific extensions in the domains of chemistry, biology, biochemistry, and bioinformatics. SIO provides an ontological foundation for the Bio2RDF linked data for the life sciences project and is used for semantic integration and discovery for SADI-based semantic web services. SIO is freely available to all users under a creative commons by attribution license. See website for further information: http://sio.semanticscience.org .

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          Most cited references26

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          Bio2RDF: towards a mashup to build bioinformatics knowledge systems.

          Presently, there are numerous bioinformatics databases available on different websites. Although RDF was proposed as a standard format for the web, these databases are still available in various formats. With the increasing popularity of the semantic web technologies and the ever growing number of databases in bioinformatics, there is a pressing need to develop mashup systems to help the process of bioinformatics knowledge integration. Bio2RDF is such a system, built from rdfizer programs written in JSP, the Sesame open source triplestore technology and an OWL ontology. With Bio2RDF, documents from public bioinformatics databases such as Kegg, PDB, MGI, HGNC and several of NCBI's databases can now be made available in RDF format through a unique URL in the form of http://bio2rdf.org/namespace:id. The Bio2RDF project has successfully applied the semantic web technology to publicly available databases by creating a knowledge space of RDF documents linked together with normalized URIs and sharing a common ontology. Bio2RDF is based on a three-step approach to build mashups of bioinformatics data. The present article details this new approach and illustrates the building of a mashup used to explore the implication of four transcription factor genes in Parkinson's disease. The Bio2RDF repository can be queried at http://bio2rdf.org.
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            The Semantic Web Revisited

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              Modeling biomedical experimental processes with OBI

              Background Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval. Results The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI. Conclusion We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components. Availability OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl
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                Author and article information

                Contributors
                Journal
                J Biomed Semantics
                J Biomed Semantics
                Journal of Biomedical Semantics
                BioMed Central
                2041-1480
                2014
                6 March 2014
                : 5
                : 14
                Affiliations
                [1 ]Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
                [2 ]Department of Computer Science and Applied Statistics, University of New Brunswick, Saint John, New Brunswick, Canada
                [3 ]Ontario Institute for Cancer Research, Toronto, Ontario, Canada
                [4 ]Department of Biology, Carleton University, Ottawa, Ontario, Canada
                [5 ]Cyber-ShARE Center of Excellence, University of Texas at El Paso, El Paso, Texas, USA
                [6 ]School of Computer Science, University of Manchester, Manchester, UK
                [7 ]Hospital del Mar Medical Research Institute, Universitat Pompeu Fabra, Barcelona, Spain
                [8 ]Digital Enterprise Research Institute, National University of Ireland, Galway, Ireland
                [9 ]Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York, USA
                [10 ]Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
                [11 ]Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid, Spain
                [12 ]Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
                Article
                2041-1480-5-14
                10.1186/2041-1480-5-14
                4015691
                24602174
                c26d9b74-1cf0-4cf5-98b1-274f97839796
                Copyright © 2014 Dumontier et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

                History
                : 2 July 2013
                : 2 February 2014
                Categories
                Database

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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