Learning from low-rank multimodal representations for predicting disease-drug associations
Abstract Background Disease-drug associations provide essential information for drug discovery and disease treatment. Many disease-drug associations remain unobserved or unknown, and trials to confirm these associations are time-consuming and expensive. To better understand and explore these valuabl...
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Autores principales: | , , , , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
BMC
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/5ff8c9e48d6041029f17dc26c75b30c0 |
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