Schenk Ryan

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Schenk
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Ryan
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  • Article
    LigerCat : using “MeSH clouds” from journal, article, or gene citations to facilitate the identification of relevant biomedical literature
    (American Medical Informatics Association, 2009-11-14) Sarkar, Indra Neil ; Schenk, Ryan ; Miller, Holly ; Norton, Cathy N.
    The identification of relevant literature from within large collections is often a challenging endeavor. In the context of indexed resources, such as MEDLINE, it has been shown that keywords from a controlled vocabulary (e.g., MeSH) can be used in combination to retrieve relevant search results. One effective strategy for identifying potential search terms is to examine a collection of documents for frequently occurring terms. In this way, “Tag clouds” are a popular mechanism for ascertaining terms associated with a collection of documents. Here, we present the Literature and Genomic Electronic Resource Catalogue (LigerCat) system for exploring biomedical literature through the selection of terms within a “MeSH cloud” that is generated based on an initial query using journal, article, or gene data. The resultant interface is encapsulated within a Web interface: http://ligercat.ubio.org. The system is also available for installation under an MIT license.
  • Article
    Exploring historical trends using taxonomic name metadata
    (BioMed Central, 2008-05-13) Sarkar, Indra Neil ; Schenk, Ryan ; Norton, Cathy N.
    Authority and year information have been attached to taxonomic names since Linnaean times. The systematic structure of taxonomic nomenclature facilitates the ability to develop tools that can be used to explore historical trends that may be associated with taxonomy. From the over 10.7 million taxonomic names that are part of the uBio system, approximately 3 million names were identified to have taxonomic authority information from the years 1750 to 2004. A pipe-delimited file was then generated, organized according to a Linnaean hierarchy and by years from 1750 to 2004, and imported into an Excel workbook. A series of macros were developed to create an Excel-based tool and a complementary Web site to explore the taxonomic data. A cursory and speculative analysis of the data reveals observable trends that may be attributable to significant events that are of both taxonomic (e.g., publishing of key monographs) and societal importance (e.g., world wars). The findings also help quantify the number of taxonomic descriptions that may be made available through digitization initiatives. Temporal organization of taxonomic data can be used to identify interesting biological epochs relative to historically significant events and ongoing efforts. We have developed an Excel workbook and complementary Web site that enables one to explore taxonomic trends for Linnaean taxonomic groupings, from Kingdoms to Families.