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...

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Detalles Bibliográficos
Autores principales: Zheng, Yi, Peng, Hui, Zhang, Xiaocai, Zhao, Zhixun, Gao, Xiaoying, Li, Jinyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
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

Internet

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

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