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SemMedDB specifications

Information


Unique identifier OMICS_12963
Name SemMedDB
Alternative name Semantic Medline Database
Restrictions to use Academic or non-commercial use
Database management system MySQL
Community driven No
Data access File download, Browse
User data submission Not allowed
Maintained Yes

Maintainer


  • person_outline Halil Kilicoglu

Publication for Semantic Medline Database

SemMedDB citations

 (3)
library_books

MELODI: Mining Enriched Literature Objects to Derive Intermediates

2018
Int J Epidemiol
PMCID: 5913624
PMID: 29342271
DOI: 10.1093/ije/dyx251

[…] SH term has been annotated as a main MeSH term in the article set, compared with the frequency of the main MeSH terms across all articles in MEDLINE (calculated from the entire set of MeSH data). For SemMedDB, two alternative analysis methods are available. The first is very similar to the MeSH approach, using the single SemMedDB terms (extracted from the triples) and then identifying enriched ter […]

library_books

Assigning factuality values to semantic relations extracted from biomedical research literature

2017
PLoS One
PMCID: 5497973
PMID: 28678823
DOI: 10.1371/journal.pone.0179926

[…] de for the best performing compositional approach is made publicly available as a component of the Bio-SCoRes framework (https://github.com/kilicogluh/Bio-SCoRes/) [] and it will be incorporated into SemMedDB [], so that researchers who exploit this repository can take advantage of the factuality feature to potentially enhance their methods. For example, rather than treating all predications equal […]

library_books

Augmenting Microarray Data with Literature Based Knowledge to Enhance Gene Regulatory Network Inference

2014
PLoS Comput Biol
PMCID: 4055569
PMID: 24921649
DOI: 10.1371/journal.pcbi.1003666

[…] d on a specific linguistic structure (nominalizations) and reported 75% precision and 57% recall . The entire MEDLINE database has been preprocessed with SemRep for efficient access, resulting in the SemMedDB database, which contains more than 57 million predications extracted from 21 million citations, as of June 30, 2012 . By normalizing free text to semantic predications, SemRep provides the ab […]

Citations

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SemMedDB institution(s)
Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD, USA
SemMedDB funding source(s)
This research was supported in part by the Intramural Research Program of the National Institutes of Health, National Library of Medicine.

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