DropDAE: Denosing Autoencoder with Contrastive Learning for Addressing Dropout Events in scRNA-seq Data
Single-cell RNA sequencing (scRNA-seq) has revolutionized molecular biology and genomics by enabling the profiling of individual cell types, providing insights into cellular heterogeneity. Deep learning methods have become popular in single cell analysis for tasks such as dimension reduction, cell c...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2025-07-01
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| coleção: | Bioengineering |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2306-5354/12/8/829 |
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