Literature DB >> 14728193

The UMLS Semantic Network and the Semantic Web.

Vipul Kashyap1.   

Abstract

The Unified Medical Language System is an extensive source of biomedical knowledge developed and maintained by the US National Library of Medicine (NLM) and is being currently used in a wide variety of biomedical applications. The Semantic Network, a component of the UMLS is a structured description of core biomedical knowledge consisting of well defined semantic types and relationships between them. We investigate the expressiveness of DAML+OIL, a markup language proposed for ontologies on the Semantic Web, for representing the knowledge contained in the Semantic Network. Requirements specific to the Semantic Network, such as polymorphic relationships and blocking relationship inheritance are discussed and approaches to represent these in DAML+OIL are presented. Finally, conclusions are presented along with a discussion of ongoing and future work.

Mesh:

Year:  2003        PMID: 14728193      PMCID: PMC1480032     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  4 in total

1.  Building a bioinformatics ontology using OIL.

Authors:  Robert Stevens; Carole Goble; Ian Horrocks; Sean Bechhofer
Journal:  IEEE Trans Inf Technol Biomed       Date:  2002-06

2.  The representation of meaning in the UMLS.

Authors:  A T McCray; S J Nelson
Journal:  Methods Inf Med       Date:  1995-03       Impact factor: 2.176

3.  The Unified Medical Language System.

Authors:  D A Lindberg; B L Humphreys; A T McCray
Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176

4.  Lexical methods for managing variation in biomedical terminologies.

Authors:  A T McCray; S Srinivasan; A C Browne
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1994
  4 in total
  2 in total

Review 1.  An introduction to the Semantic Web for health sciences librarians.

Authors:  Ioana Robu; Valentin Robu; Benoit Thirion
Journal:  J Med Libr Assoc       Date:  2006-04

2.  Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships.

Authors:  Xiaoyan A Qu; Ranga C Gudivada; Anil G Jegga; Eric K Neumann; Bruce J Aronow
Journal:  BMC Bioinformatics       Date:  2009-05-06       Impact factor: 3.169

  2 in total

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