7 found
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Lindsay Cowell [3]Lindsay G. Cowell [3]Lindsay Grey Cowell [1]
  1. Towards an Ontological Representation of Resistance: The Case of MRSA.Albert Goldfain, Barry Smith & Lindsay G. Cowell - 2011 - Journal of Biomedical Informatics 44 (1):35-41.
    This paper addresses a family of issues surrounding the biological phenomenon of resistance and its representation in realist ontologies. The treatments of resistance terms in various existing ontologies are examined and found to be either overly narrow, internally inconsistent, or otherwise problematic. We propose a more coherent characterization of resistance in terms of what we shall call blocking dispositions, which are collections of mutually coordinated dispositions which are of such a sort that they cannot undergo simultaneous realization within a single (...)
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  2. Infectious Disease Ontology.Lindsay Grey Cowell & Barry Smith - 2009 - In Infectious Disease Informatics. New York: Springer New York. pp. 373-395.
    Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and (...)
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  3.  65
    An Improved Ontological Representation of Dendritic Cells as a Paradigm for All Cell Types.Anna Maria Masci, Cecilia N. Arighi, Alexander D. Diehl, Anne E. Liebermann, Chris Mungall, Richard H. Scheuermann, Barry Smith & Lindsay Cowell - 2009 - BMC Bioinformatics 10 (1):70.
    Recent increases in the volume and diversity of life science data and information and an increasing emphasis on data sharing and interoperability have resulted in the creation of a large number of biological ontologies, including the Cell Ontology (CL), designed to provide a standardized representation of cell types for data annotation. Ontologies have been shown to have significant benefits for computational analyses of large data sets and for automated reasoning applications, leading to organized attempts to improve the structure and formal (...)
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  4.  42
    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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  5.  33
    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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  6.  51
    Clonal Complexes in Biomedical Ontologies.Albert Goldfain, Lindsay Cowell & Barry Smith - 2009 - In ICBO 2009: Proceedings of the First International Conference on Biomedical Ontology. pp. 168.
    An accurate classification of bacteria is essential for the proper identification of patient infections and subsequent treatment decisions. Multi-Locus Sequence Typing (MLST) is a genetic technique for bacterial classification. MLST classifications are used to cluster bacteria into clonal complexes. Importantly, clonal complexes can serve as a biological species concept for bacteria, facilitating an otherwise difficult taxonomic classification. In this paper, we argue for the inclusion of terms relating to clonal complexes in biomedical ontologies.
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  7.  37
    Ontological Representation of CDC Active Bacterial Core Surveillance Case Reports.Albert Goldfain, Barry Smith & Lindsay G. Cowell - 2014 - Proceedings of the Fifth International Conference on Biomedical Ontology 1327:74-77.
    The Center for Disease Control and Prevention’s Active Bacterial Core Surveillance (CDC ABCs) Program is a collaborative effort betweeen the CDC, state health departments, laboratories, and universities to track invasive bacterial pathogens of particular importance to public health [1]. The year-end surveillance reports produced by this program help to shape public policy and coordinate responses to emerging infectious diseases over time. The ABCs case report form (CRF) data represents an excellent opportunity for data reuse beyond the original surveillance purposes.
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