SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost
Abstract Background Identifying miRNA and disease associations helps us understand disease mechanisms of action from the molecular level. However, it is usually blind, time-consuming, and small-scale based on biological experiments. Hence, developing computational methods to predict unknown miRNA an...
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| Автори: | , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
BMC
2021-04-01
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| Серія: | BMC Bioinformatics |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1186/s12859-021-04135-2 |
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