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DDI-PULearn: a positive-unlabeled learning method for large-scale prediction of drug-drug interactions
BACKGROUND: Drug-drug interactions (DDIs) are a major concern in patients’ medication. It’s unfeasible to identify all potential DDIs using experimental methods which are time-consuming and expensive. Computational methods provide an effective strategy, however, facing challenges due to the lack of...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929327/ https://www.ncbi.nlm.nih.gov/pubmed/31870276 http://dx.doi.org/10.1186/s12859-019-3214-6 |