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  1. The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration.Barry Smith, Michael Ashburner, Cornelius Rosse, Jonathan Bard, William Bug, Werner Ceusters, Louis J. Goldberg, Karen Eilbeck, Amelia Ireland, Christopher J. Mungall, Neocles Leontis, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Nigam Shah, Patricia L. Whetzel & Suzanna Lewis - 2007 - Nature Biotechnology 25 (11):1251-1255.
    The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or ‘ontologies’. Unfortunately, the very success of this approach has led to a proliferation of ontologies which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium has set in train a strategy to overcome this problem. Existing (...)
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  • National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge.Daniel L. Rubin, Suzanna E. Lewis, Chris J. Mungall, Misra Sima, Westerfield Monte, Ashburner Michael, Christopher G. Chute, Ida Sim, Harold Solbrig, M. A. Storey, Barry Smith, John D. Richter, Natasha Noy & Mark A. Musen - 2006 - Omics: A Journal of Integrative Biology 10 (2):185-198.
    The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create (...)
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  • Framework for a protein ontology.Darren A. Natale, Cecilia N. Arighi, Winona Barker, Judith Blake, Ti-Cheng Chang, Zhangzhi Hu, Hongfang Liu, Barry Smith & Cathy H. Wu - 2007 - BMC Bioinformatics 8 (Suppl 9):S1.
    Biomedical ontologies are emerging as critical tools in genomic and proteomic research where complex data in disparate resources need to be integrated. A number of ontologies exist that describe the properties that can be attributed to proteins; for example, protein functions are described by Gene Ontology, while human diseases are described by Disease Ontology. There is, however, a gap in the current set of ontologies—one that describes the protein entities themselves and their relationships. We have designed a PRotein Ontology (PRO) (...)
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  • The Protein Ontology: A structured representation of protein forms and complexes.Darren Natale, Cecilia N. Arighi, Winona C. Barker, Judith A. Blake, Carol J. Bult, Michael Caudy, Harold J. Drabkin, Peter D’Eustachio, Alexei V. Evsikov, Hongzhan Huang, Jules Nchoutmboube, Natalia V. Roberts, Barry Smith, Jian Zhang & Cathy H. Wu - 2011 - Nucleic Acids Research 39 (1):D539-D545.
    The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results of protein (...)
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  • Relations in Biomedical Ontologies.Barry Smith, Werner Ceusters, Bert Klagges, Jacob Köhler, Anand Kuma, Jane Lomax, Chris Mungall, , Fabian Neuhaus, Alan Rector & Cornelius Rosse - 2005 - Genome Biology 6 (5):R46.
    To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.
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  • Gene Ontology: Tool for the unification of biology.M. Ashburner - 2000 - Nature Genetics 25:25-29.
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