18 found
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  1.  56
    Guidelines for Writing Definitions in Ontologies.Selja Seppälä, Alan Ruttenberg & Barry Smith - 2017 - Ciência da Informação 46 (1): 73-88.
    Ontologies are being used increasingly to promote the reusability of scientific information by allowing heterogeneous data to be integrated under a common, normalized representation. Definitions play a central role in the use of ontologies both by humans and by computers. Textual definitions allow ontologists and data curators to understand the intended meaning of ontology terms and to use these terms in a consistent fashion across contexts. Logical definitions allow machines to check the integrity of ontologies and reason over data annotated (...)
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  2.  50
    The Development of Non-Coding RNA Ontology.Jingshan Huang, Karen Eilbeck, Barry Smith, Judith Blake, Deijing Dou, Weili Huang, Darren Natale, Alan Ruttenberg, Jun Huan, Michael Zimmermann, Guoqian Jiang, Yu Lin, Bin Wu, Harrison Strachan, Nisansa de Silva & Mohan Vamsi Kasukurthi - 2016 - International Journal of Data Mining and Bioinformatics 15 (3):214--232.
    Identification of non-coding RNAs (ncRNAs) has been significantly improved over the past decade. On the other hand, semantic annotation of ncRNA data is facing critical challenges due to the lack of a comprehensive ontology to serve as common data elements and data exchange standards in the field. We developed the Non-Coding RNA Ontology (NCRO) to handle this situation. By providing a formally defined ncRNA controlled vocabulary, the NCRO aims to fill a specific and highly needed niche in semantic annotation of (...)
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  3.  91
    Definitions in Ontologies.Selja Seppälä, Alan Ruttenberg, Yonatan Schreiber & Barry Smith - 2016 - Cahiers de Lexicologie 109 (2):175‐207.
    Definitions vary according to context of use and target audience. They must be made relevant for each context to fulfill their cognitive and linguistic goals. This involves adapting their logical structure, type of content, and form to each context of use. We examine from these perspectives the case of definitions in ontologies.
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  4.  40
    Toll-Like Receptor Signaling in Vertebrates: Testing the Integration of Protein, Complex, and Pathway Data in the Protein Ontology Framework.Cecilia Arighi, Veronica Shamovsky, Anna Maria Masci, Alan Ruttenberg, Barry Smith, Darren Natale, Cathy Wu & Peter D’Eustachio - 2015 - PLoS ONE 10 (4):e0122978.
    The Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology and annotation data set (...)
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  5.  34
    The Ontology for Biomedical Investigations.Anita Bandrowski, Ryan Brinkman, Mathias Brochhausen, Matthew H. Brush, Bill Bug, Marcus C. Chibucos, Kevin Clancy, Mélanie Courtot, Dirk Derom, Michel Dumontier, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Frank Gibson, Alejandra Gonzalez-Beltran, Melissa A. Haendel, Yongqun He, Mervi Heiskanen, Tina Hernandez-Boussard, Mark Jensen, Yu Lin, Allyson L. Lister, Phillip Lord, James Malone, Elisabetta Manduchi, Monnie McGee, Norman Morrison, James A. Overton, Helen Parkinson, Bjoern Peters, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Daniel Schober, Barry Smith, Larisa N. Soldatova, Christian J. Stoeckert, Chris F. Taylor, Carlo Torniai, Jessica A. Turner, Randi Vita, Patricia L. Whetzel & Jie Zheng - 2016 - PLoS ONE 11 (4):e0154556.
    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...)
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  6.  38
    Developing the Quantitative Histopathology Image Ontology : A Case Study Using the Hot Spot Detection Problem.Metin Gurcan, Tomaszewski N., Overton John, A. James, Scott Doyle, Alan Ruttenberg & Barry Smith - 2017 - Journal of Biomedical Informatics 66:129-135.
    Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection with (...)
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  7.  23
    A Domain Ontology for the Non-Coding RNA Field.Jingshan Huang, Karen Eilbeck, Judith A. Blake, Dejing Dou, Darren A. Natale, Alan Ruttenberg, Barry Smith, Michael T. Zimmermann, Guoqian Jiang & Yu Lin - 2015 - In IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015). pp. 621-624.
    Identification of non-coding RNAs (ncRNAs) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncRNA data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a precisely defined ncRNA controlled vocabulary, which can fill a specific and highly needed niche in unification of ncRNA biology.
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  8.  19
    The ImmPort Antibody Ontology.William Duncan, Travis Allen, Jonathan Bona, Olivia Helfer, Barry Smith, Alan Ruttenberg & Alexander D. Diehl - 2016 - Proceedings of the International Conference on Biological Ontology 1747.
    Monoclonal antibodies are essential biomedical research and clinical reagents that are produced by companies and research laboratories. The NIAID ImmPort (Immunology Database and Analysis Portal) resource provides a long-term, sustainable data warehouse for immunological data generated by NIAID, DAIT and DMID funded investigators for data archiving and re-use. A variety of immunological data is generated using techniques that rely upon monoclonal antibody reagents, including flow cytometry, immunofluorescence, and ELISA. In order to facilitate querying, integration, and reuse of data, standardized terminology (...)
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  9. The Neurological Disease Ontology.Mark Jensen, Alexander P. Cox, Naveed Chaudhry, Marcus Ng, Donat Sule, William Duncan, Patrick Ray, Bianca Weinstock-Guttman, Barry Smith, Alan Ruttenberg, Kinga Szigeti & Alexander D. Diehl - 2013 - Journal of Biomedical Semantics 4 (42).
    We are developing the Neurological Disease Ontology (ND) to provide a framework to enable representation of aspects of neurological diseases that are relevant to their treatment and study. ND is a representational tool that addresses the need for unambiguous annotation, storage, and retrieval of data associated with the treatment and study of neurological diseases. ND is being developed in compliance with the Open Biomedical Ontology Foundry principles and builds upon the paradigm established by the Ontology for General Medical Science (OGMS) (...)
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  10.  17
    VO: Vaccine Ontology.Yongqun He, Lindsay Cowell, Alexander D. Diehl, H. L. Mobley, Bjoern Peters, Alan Ruttenberg, Richard H. Scheuermann, Ryan R. Brinkman, Melanie Courtot, Chris Mungall, Barry Smith & Others - 2009 - In ICBO 2009: Proceedings of the First International Conference on Biomedical Ontology. Buffalo:
    Vaccine research, as well as the development, testing, clinical trials, and commercial uses of vaccines involve complex processes with various biological data that include gene and protein expression, analysis of molecular and cellular interactions, study of tissue and whole body responses, and extensive epidemiological modeling. Although many data resources are available to meet different aspects of vaccine needs, it remains a challenge how we are to standardize vaccine annotation, integrate data about varied vaccine types and resources, and support advanced vaccine (...)
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  11.  67
    Ontology and the Future of Dental Research Informatics.Barry Smith, Louis J. Goldberg, Alan Ruttenberg & Michael Glick - 2010 - Journal of the American Dental Association 141 (10):1173-75.
    How do we find what is clinically significant in the swarms of data being generated by today’s diagnostic technologies? As electronic records become ever more prevalent – and digital imaging and genomic, proteomic, salivaomics, metabalomics, pharmacogenomics, phenomics and transcriptomics techniques become commonplace – fdifferent clinical and biological disciplines are facing up to the need to put their data houses in order to avoid the consequences of an uncontrolled explosion of different ways of describing information. We describe a new strategy to (...)
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  12.  13
    Towards a Body Fluids Ontology: A Unified Application Ontology for Basic and Translational Science.Jiye Ai, Mauricio Barcellos Almeida, André Queiroz De Andrade, Alan Ruttenberg, David Tai Wai Wong & Barry Smith - 2011 - Second International Conference on Biomedical Ontology , Buffalo, Ny 833:227-229.
    We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...)
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  13.  13
    The Representation of Protein Complexes in the Protein Ontology.Carol Bult, Harold Drabkin, Alexei Evsikov, Darren Natale, Cecilia Arighi, Natalia Roberts, Alan Ruttenberg, Peter D’Eustachio, Barry Smith, Judith Blake & Cathy Wu - 2011 - BMC Bioinformatics 12 (371):1-11.
    Representing species-specific proteins and protein complexes in ontologies that are both human and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because (...)
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  14.  12
    Ontologies for the Study of Neurological Disease.Alexander P. Cox, Mark Jensen, William Duncan, Bianca Weinstock-Guttman, Kinga Szigeti, Alan Ruttenberg, Barry Smith & Alexander D. Diehl - 2012 - In Towards an Ontology of Mental Functioning (ICBO Workshop), Third International Conference on Biomedical Ontology. Graz:
    We have begun work on two separate but related ontologies for the study of neurological diseases. The first, the Neurological Disease Ontology (ND), is intended to provide a set of controlled, logically connected classes to describe the range of neurological diseases and their associated signs and symptoms, assessments, diagnoses, and interventions that are encountered in the course of clinical practice. ND is built as an extension of the Ontology for General Medical Sciences — a high-level candidate OBO Foundry ontology that (...)
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  15. MIREOT: The Minimum Information to Reference an External Ontology Term.Mélanie Courtot, Frank Gibson, Allyson L. Lister, James Malone, Daniel Schober, Ryan R. Brinkman & Alan Ruttenberg - 2011 - Applied Ontology 6 (1):23-33.
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  16.  62
    An Axiomatisation of Basic Formal Ontology with Projection Functions.Kerry Trentelman, Alan Ruttenberg & Barry Smith - 2010 - In Kerry Taylor (ed.), Advances in Ontologies, Proceedings of the Sixth Australasian Ontology Workshop. University of Adelaide. pp. 71-80.
    This paper proposes a reformulation of the treatment of boundaries, at parts and aggregates of entities in Basic Formal Ontology. These are currently treated as mutually exclusive, which is inadequate for biological representation since some entities may simultaneously be at parts, boundaries and/or aggregates. We introduce functions which map entities to their boundaries, at parts or aggregations. We make use of time, space and spacetime projection functions which, along the way, allow us to develop a simple temporal theory.
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  17.  16
    Overcoming the Ontology Enrichment Bottleneck with Quick Term Templates.Philippe Rocca-Serra, Alan Ruttenberg, Martin J. O'Connor, Patricia L. Whetzel, Daniel Schober, Jay Greenbaum, Mélanie Courtot, Ryan R. Brinkman, Susanna Assunta Sansone & Richard Scheuermann - 2011 - Applied Ontology 6 (1):13-22.
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  18.  1
    More About Ontology: Response.Barry Smith, Louis Goldberg, Michael Glick & Alan Ruttenberg - 2011 - Journal of the American Dental Association 142 (3):252-254.
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