Literature DB >> 12603048

Linking biomedical language information and knowledge resources: GO and UMLS.

I N Sarkar1, M N Cantor, R Gelman, F Hartel, Y A Lussier.   

Abstract

Integration of various informatics terminologies will be an essential activity towards supporting the advancement of both the biomedical and clinical sciences. The GO consortium has developed an impressive collection of biomedical terms specific to genes and proteins in a variety of organisms. The UMLS is a composite collection of various medical terminologies, pioneered by the National Library of Medicine. In the present study, we examine a variety of techniques for mapping terms from one terminology (GO) to another (UMLS), and describe their respective performances for a small, curated data set attained from the National Cancer Institute, which had precision values ranging from 30% (100% recall) to 95% (74% recall). Based on each technique's performance, we comment on how each can be used to enrich an existing terminology (UMLS) in future studies and how linking biological terminologies to UMLS differs from linking medical terminologies.

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Year:  2003        PMID: 12603048      PMCID: PMC2916681          DOI: 10.1142/9789812776303_0041

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  24 in total

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  17 in total

1.  An evaluation of hybrid methods for matching biomedical terminologies: mapping the gene ontology to the UMLS.

Authors:  M N Cantor; I N Sarkar; R Gelman; F Hartel; O Bodenreider; Y A Lussier
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2.  Putting data integration into practice: using biomedical terminologies to add structure to existing data sources.

Authors:  Michael N Cantor; Yves A Lussier
Journal:  AMIA Annu Symp Proc       Date:  2003

3.  Automating terminological networks to link heterogeneous biomedical databases.

Authors:  Xiaoyan Wang; Hui Nar Quek; Michael Cantor; Pauline Kra; Aylit Schultz; Yves A Lussier
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4.  Terminological mapping for high throughput comparative biology of phenotypes.

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Journal:  Pac Symp Biocomput       Date:  2004

5.  Visualizing information across multidimensional post-genomic structured and textual databases.

Authors:  Ying Tao; Carol Friedman; Yves A Lussier
Journal:  Bioinformatics       Date:  2004-12-14       Impact factor: 6.937

6.  PhenoGO: assigning phenotypic context to gene ontology annotations with natural language processing.

Authors:  Yves Lussier; Tara Borlawsky; Daniel Rappaport; Yang Liu; Carol Friedman
Journal:  Pac Symp Biocomput       Date:  2006

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Authors:  Helen L Johnson; K Bretonnel Cohen; William A Baumgartner; Zhiyong Lu; Michael Bada; Todd Kester; Hyunmin Kim; Lawrence Hunter
Journal:  Pac Symp Biocomput       Date:  2006

Review 8.  Computational approaches to phenotyping: high-throughput phenomics.

Authors:  Yves A Lussier; Yang Liu
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9.  A fault model for ontology mapping, alignment, and linking systems.

Authors:  Helen L Johnson; K Bretonnel Cohen; Lawrence Hunter
Journal:  Pac Symp Biocomput       Date:  2007

10.  Identifying natural health product and dietary supplement information within adverse event reporting systems.

Authors:  Vivekanand Sharma; Indra Neil Sarkar
Journal:  Pac Symp Biocomput       Date:  2018
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