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Database Commons - MEDIC

MEDIC

Citations: 54

z-index 9.00

Short name MEDIC
Full name CTD's MEDIC disease vocabulary
Description CTD's MEDIC disease vocabulary is a modified subset of descriptors from the “Diseases” [C] branch of the U.S. National Library of Medicine's Medical Subject Headings (MeSH®), combined with genetic disorders from the Online Mendelian Inheritance in Man® (OMIM®) database.MEDIC is structured as a polyhierarchic tree in which a term may appear as a node in more than one branch. A disease may have different descendants in each branch in which it appears .
URL http://ctdbase.org/voc.go?type=disease
Year founded 2012
Last update & version 2012-02-12    
Availability Free to all users
University/Institution hosted The Mount Desert Island Biological Laboratory
Address Salisbury Cove,ME 04672,USA
City Salisbury Cove
Province/State ME
Country/Region United States
Contact name Allan Peter Davis
Contact email apd@mdibl.org
Data type(s)
Major organism(s)
Keyword(s)
  • toxicogenomics
Publication(s)
  • MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database. [PMID: 22434833]

    Allan Peter Davis, Thomas C Wiegers, Michael C Rosenstein, Carolyn J Mattingly
    Database : the journal of biological databases and curation 2012:2012
    54 Citations (Google Scholar as of 2016-01-27)

    Abstract: The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the effects of environmental chemicals on human health. CTD biocurators manually curate a triad of chemical-gene, chemical-disease and gene-disease relationships from the scientific literature. The CTD curation paradigm uses controlled vocabularies for chemicals, genes and diseases. To curate disease information, CTD first had to identify a source of controlled terms. Two resources seemed to be good candidates: the Online Mendelian Inheritance in Man (OMIM) and the 'Diseases' branch of the National Library of Medicine's Medical Subject Headers (MeSH). To maximize the advantages of both, CTD biocurators undertook a novel initiative to map the flat list of OMIM disease terms into the hierarchical nature of the MeSH vocabulary. The result is CTD's 'merged disease vocabulary' (MEDIC), a unique resource that integrates OMIM terms, synonyms and identifiers with MeSH terms, synonyms, definitions, identifiers and hierarchical relationships. MEDIC is both a deep and broad vocabulary, composed of 9700 unique diseases described by more than 67?000 terms (including synonyms). It is freely available to download in various formats from CTD. While neither a true ontology nor a perfect solution, this vocabulary has nonetheless proved to be extremely successful and practical for our biocurators in generating over 2.5 million disease-associated toxicogenomic relationships in CTD. Other external databases have also begun to adopt MEDIC for their disease vocabulary. Here, we describe the construction, implementation, maintenance and use of MEDIC to raise awareness of this resource and to offer it as a putative scaffold in the formal construction of an official disease ontology. DATABASE URL: http://ctd.mdibl.org/voc.go?type=disease.

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Rate of accessibility:
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200 OK2018-04-03
200 OK2018-02-27
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200 OK2018-02-20
200 OK2018-02-16
200 OK2018-02-13
200 OK2018-02-09
200 OK2018-02-06
200 OK2018-02-02
200 OK2018-01-30
200 OK2018-01-26
200 OK2018-01-23
200 OK2018-01-19
200 OK2018-01-16
200 OK2018-01-12
200 OK2018-01-09
200 OK2018-01-05
200 OK2018-01-02
200 OK2017-12-29
200 OK2017-12-26
200 OK2017-12-22
200 OK2017-12-19
200 OK2017-12-15
200 OK2017-12-12
200 OK2017-12-08
200 OK2017-12-05
200 OK2017-12-01
200 OK2017-11-28
200 OK2017-11-24
200 OK2017-11-21
200 OK2017-11-17
200 OK2017-11-14
200 OK2017-11-10
200 OK2017-11-07
200 OK2017-11-03
200 OK2017-10-31
200 OK2017-10-27
200 OK2017-10-24
200 OK2017-10-20
200 OK2017-10-17
200 OK2017-10-13
200 OK2017-10-10
200 OK2017-10-06
200 OK2017-10-03
200 OK2017-09-29
200 OK2017-09-26
200 OK2017-09-22
200 OK2017-09-19
200 OK2017-09-15
200 OK2017-09-12
200 OK2017-09-08
200 OK2017-09-05
200 OK2017-09-01
200 OK2017-08-29
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200 OK2017-08-22
200 OK2017-08-18
200 OK2017-08-15
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200 OK2017-08-08
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200 OK2017-03-28
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200 OK2017-03-17
200 OK2017-03-14
200 OK2017-03-10
200 OK2017-03-07
200 OK2017-03-03
200 OK2017-02-28
200 OK2017-02-24
200 OK2017-02-21
200 OK2017-02-17
200 OK2017-02-14
200 OK2017-02-10
200 OK2017-02-07
200 OK2017-02-03
200 OK2017-01-31
200 OK2017-01-27
200 OK2017-01-24
200 OK2017-01-20
200 OK2017-01-17
200 OK2017-01-13
200 OK2017-01-10
200 OK2017-01-06
200 OK2017-01-03
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200 OK2016-12-09
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200 OK2016-11-18
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200 OK2016-11-11
200 OK2016-11-08
200 OK2016-11-04
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200 OK2016-10-28
200 OK2016-10-25
200 OK2016-10-21
200 OK2016-10-18
200 OK2016-10-14
200 OK2016-10-11
200 OK2016-10-07
200 OK2016-10-04
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200 OK2016-09-27
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200 OK2016-09-20
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200 OK2016-08-19
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200 OK2016-08-09
200 OK2016-08-05
200 OK2016-08-02
200 OK2016-07-29
200 OK2016-07-26
200 OK2016-07-22
200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
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200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
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200 OK2016-04-15
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200 OK2016-03-29
200 OK2016-03-28
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200 OK2016-03-23
200 OK2016-03-21
200 OK2016-03-18
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200 OK2016-03-14
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200 OK2016-03-07
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200 OK2016-03-02
200 OK2016-02-29
200 OK2016-02-26
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200 OK2016-02-15
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200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
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200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
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200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04

Tags

Disease
Animal Bacteria Homo sapiens
toxicogenomics

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Lin Liu [2016-03-26]
    • Li Yang [2015-06-26]
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