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  1. 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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  • Saliva Ontology: An Ontology-Based Framework for a Salivaomics Knowledge Base.Jiye Ai, Barry Smith & David Wong - 2010 - BMC Bioinformatics 11 (1):302.
    The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...)
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  • 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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  • The Ontology of Biological and Clinical Statistics (OBCS) for Standardized and Reproducible Statistical Analysis.Jie Zheng, Marcelline R. Harris, Anna Maria Masci, Lin Yu, Alfred Hero, Barry Smith & Yongqun He - 2016 - Journal of Biomedical Semantics 7 (53).
    Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data visualization’, ‘statistical data (...)
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  • 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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  • 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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  • Constructing a Lattice of Infectious Disease Ontologies From a Staphylococcus Aureus Isolate Repository.Albert Goldfain, Lindsay G. Cowell & Barry Smith - 2012 - In Proceeedings of the Third International Conference on Biomedical Ontology (CEUR 897).
    A repository of clinically associated Staphylococcus aureus (Sa) isolates is used to semi‐automatically generate a set of application ontologies for specific subfamilies of Sa‐related disease. Each such application ontology is compatible with the Infectious Disease Ontology (IDO) and uses resources from the Open Biomedical Ontology (OBO) Foundry. The set of application ontologies forms a lattice structure beneath the IDO‐Core and IDO‐extension reference ontologies. We show how this lattice can be used to define a strategy for the construction of a new (...)
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  • Biomedical Imaging Ontologies: A Survey and Proposal for Future Work.Barry Smith, Sivaram Arabandi, Mathias Brochhausen, Michael Calhoun, Paolo Ciccarese, Scott Doyle, Bernard Gibaud, Ilya Goldberg, Charles E. Kahn Jr, James Overton, John Tomaszewski & Metin Gurcan - 2015 - Journal of Pathology Informatics 6 (37):37.
    Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged data. Aim: This (...)
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  • A Plant Disease Extension of the Infectious Disease Ontology.Ramona Walls, Barry Smith, Elser Justin, Goldfain Albert & W. Stevenson Dennis - 2012 - In Proceedings of the Third International Conference on Biomedical Ontology (CEUR 897). pp. 1-5.
    Plants from a handful of species provide the primary source of food for all people, yet this source is vulnerable to multiple stressors, such as disease, drought, and nutrient deficiency. With rapid population growth and climate uncertainty, the need to produce crops that can tolerate or resist plant stressors is more crucial than ever. Traditional plant breeding methods may not be sufficient to overcome this challenge, and methods such as highOthroughput sequencing and automated scoring of phenotypes can provide significant new (...)
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  • Aging Neuro-Behavior Ontology.Fernando Martínez-Santiago, M. Rosario García-Viedma, John A. Williams, Luke T. Slater & Georgios V. Gkoutos - 2020 - Applied Ontology 15 (2):219-239.
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  • Ontological Realism: A Methodology for Coordinated Evolution of Scientific Ontologies.Barry Smith & Werner Ceusters - 2010 - Applied Ontology 5 (3):139-188.
    Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be (...)
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  • 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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  • An Ontological Analysis of Drug Prescriptions.Jean-François Ethier, Adrien Barton & Ryeyan Taseen - 2018 - Applied Ontology 13 (4):273-294.
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  • Ontologies as Integrative Tools for Plant Science.Ramona Walls, Balaji Athreya, Laurel Cooper, Justin Elser, Maria A. Gandolfo, Pankaj Jaiswal, Christopher J. Mungall, Justin Preece, Stefan Rensing, Barry Smith & Dennis W. Stevenson - 2012 - American Journal of Botany 99 (8):1263–1275.
    Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the Semantic Web. This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, (...)
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  • Ontology Based Annotation of Contextualized Vital Signs.Goldfain Albert, Xu Min, Bona Jonathan & Barry Smith - 2013 - In Proceedings of the Fourth International Conference on Biomedical Ontology (ICBO). Montreal: pp. 28-33.
    Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system is applied (...)
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  • Vital Sign Ontology.Albert Goldfain, Barry Smith, Sivaram Arabandi, Mathias Brochhausen & William R. Hogan - 2011 - In Proceedings of the Workshop on Bio-Ontologies, ISMB, Vienna, June 2011. Vienna: pp. 71-74.
    We introduce the Vital Sign Ontology (VSO), an extension of the Ontology for General Medical Science (OGMS) that covers the consensus human vital signs: blood pressure, body temperature, respiratory rate, and pulse rate. VSO provides a controlled structured vocabulary for describing vital sign measurement data, the processes of measuring vital signs, and the anatomical entities participating in such measurements. VSO is implemented in OWL-DL and follows OBO Foundry guidelines and best practices. If properly developed and extended, we believe the VSO (...)
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  • The Blood Ontology: An Ontology in the Domain of Hematology.Almeida Mauricio Barcellos, Proietti Anna Barbara de Freitas Carneiro, Ai Jiye & Barry Smith - 2011 - In Proceedings of the Second International Conference on Biomedical Ontology, Buffalo, NY, July 28-30, 2011 (CEUR 883). pp. (CEUR Workshop Proceedings, 833).
    Despite the importance of human blood to clinical practice and research, hematology and blood transfusion data remain scattered throughout a range of disparate sources. This lack of systematization concerning the use and definition of terms poses problems for physicians and biomedical professionals. We are introducing here the Blood Ontology, an ongoing initiative designed to serve as a controlled vocabulary for use in organizing information about blood. The paper describes the scope of the Blood Ontology, its stage of development and some (...)
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  • Guest Editorial: Ontologies for Clinical and Translational Research.Barry Smith & Richard H. Scheuermann - 2011 - Journal of Biomedical Informatics 44 (1):3--7.
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