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William Duncan [6]William D. Duncan [2]
  1. OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies.Rebecca C. Jackson, Nicolas Matentzoglu, James A. Overton, Randi Vita, James P. Balhoff, Pier Luigi Buttigieg, Seth Carbon, Melanie Courtot, Alexander D. Diehl, Damion Dooley, William Duncan, Nomi L. Harris, Melissa A. Haendel, Suzanna E. Lewis, Darren A. Natale, David Osumi-Sutherland, Alan Ruttenberg, Lynn M. Schriml, Barry Smith, Christian J. Stoeckert, Nicole A. Vasilevsky, Ramona L. Walls, Jie Zheng, Christopher J. Mungall & Bjoern Peters - 2021 - BioaRxiv.
    Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the (...)
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  2. A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.Yongqun He, Hong Yu, Anthony Huffman, Asiyah Yu Lin, Darren A. Natale, John Beverley, Ling Zheng, Yehoshua Perl, Zhigang Wang, Yingtong Liu, Edison Ong, Yang Wang, Philip Huang, Long Tran, Jinyang Du, Zalan Shah, Easheta Shah, Roshan Desai, Hsin-hui Huang, Yujia Tian, Eric Merrell, William D. Duncan, Sivaram Arabandi, Lynn M. Schriml, Jie Zheng, Anna Maria Masci, Liwei Wang, Hongfang Liu, Fatima Zohra Smaili, Robert Hoehndorf, Zoë May Pendlington, Paola Roncaglia, Xianwei Ye, Jiangan Xie, Yi-Wei Tang, Xiaolin Yang, Suyuan Peng, Luxia Zhang, Luonan Chen, Junguk Hur, Gilbert S. Omenn, Brian Athey & Barry Smith - 2022 - Journal of Biomedical Semantics 13 (1):25.
    The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...)
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  3. 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):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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  4. Improving the Quality and Utility of Electronic Health Record Data through Ontologies.Asiyah Yu Lin, Sivaram Arabandi, Thomas Beale, William Duncan, Hicks D., Hogan Amanda, R. William, Mark Jensen, Ross Koppel, Catalina Martínez-Costa, Øystein Nytrø, Jihad S. Obeid, Jose Parente de Oliveira, Alan Ruttenberg, Selja Seppälä, Barry Smith, Dagobert Soergel, Jie Zheng & Stefan Schulz - 2023 - Standards 3 (3):316–340.
    The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in (...)
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  5. 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 Alexander P. Cox, Mark Jensen, William Duncan, Bianca Weinstock-Guttman, Kinga Szigeti, Alan Ruttenberg, Barry Smith & Alexander D. Diehl (eds.), 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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  6. 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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  7. Ontological Support for Living Plan Specification, Execution and Evaluation.Erik Thomsen, Fred Read, William Duncan, Tatiana Malyuta & Barry Smith - 2014 - In Erik Thomsen, Fred Read, William Duncan, Tatiana Malyuta & Barry Smith (eds.), Semantic Technology in Intelligence, Defense and Security (STIDS), CEUR vol. 1304. pp. 10-17.
    Maintaining systems of military plans is critical for military effectiveness, but is also challenging. Plans will become obsolete as the world diverges from the assumptions on which they rest. If too many ad hoc changes are made to intermeshed plans, the ensemble may no longer lead to well-synchronized and coordinated operations, resulting in the system of plans becoming itself incoherent. We describe in what follows an Adaptive Planning process that we are developing on behalf of the Air Force Research Laboratory (...)
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  8. Protein Ontology: Enhancing and scaling up the representation of protein entities.Darren A. Natale, Cecilia N. Arighi, Judith A. Blake, Jonathan Bona, Chuming Chen, Sheng-Chih Chen, Karen R. Christie, Julie Cowart, Peter D'Eustachio, Alexander D. Diehl, Harold J. Drabkin, William D. Duncan, Hongzhan Huang, Jia Ren, Karen Ross & Alan Ruttenberg - 2017 - Nucleic Acids Research 45 (D1):D339-D346.
    The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr) formally defines and describes taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. PRO thus serves as a tool for referencing protein entities at any level of specificity. To enhance this ability, and to facilitate the comparison of such entities described in different resources, we developed a standardized representation of proteoforms using UniProtKB as a sequence reference and PSI-MOD as a post-translational modification (...)
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