Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity
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Title
Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity
Authors
Keywords
Similarity Score, MeSH Term, Annotation Level, Drug Repositioning, Comparative Toxicogenomics Database
Journal
BMC Medical Genomics
Volume 6, Issue Suppl 2, Pages S3
Publisher
Springer Nature
Online
2013-05-07
DOI
10.1186/1755-8794-6-s2-s3
References
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Related references
Note: Only part of the references are listed.- Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)
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- Drug repurposing and adverse event prediction using high-throughput literature analysis
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- (2010) A. P. Davis et al. NUCLEIC ACIDS RESEARCH
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