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Screening drug-target interactions with positive-unlabeled learning
Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However, usually only positive DTIs are deposited in known databases, which challenges computational methods to predict novel DTIs due to the lack of negative samples. To overcome this dilemma, researchers usuall...
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| Publicado no: | Sci Rep |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5556112/ https://ncbi.nlm.nih.gov/pubmed/28808275 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-017-08079-7 |
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