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NeuRank: learning to rank with neural networks for drug–target interaction prediction
BACKGROUND: Experimental verification of a drug discovery process is expensive and time-consuming. Therefore, recently, the demand to more efficiently and effectively identify drug–target interactions (DTIs) has intensified. RESULTS: We treat the prediction of DTIs as a ranking problem and propose a...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620576/ https://www.ncbi.nlm.nih.gov/pubmed/34836495 http://dx.doi.org/10.1186/s12859-021-04476-y |