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Comparing a knowledge-driven approach to a supervised machine learning approach in large-scale extraction of drug-side effect relationships from free-text biomedical literature
BACKGROUND: Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. However, a comprehensive drug-SE association knowledge base does not exist. In this study, we present a novel knowledge-dr...
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| Vydáno v: | BMC Bioinformatics |
|---|---|
| Hlavní autoři: | , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
BioMed Central
2015
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4402591/ https://ncbi.nlm.nih.gov/pubmed/25860223 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-16-S5-S6 |
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