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...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Wanlin Juan, Kwang Woo Ahn, Yi-Guang Chen, Chien-Wei Lin
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2025-07-01
Edice:	Bioengineering
Témata:	dropout imputation autoencoder denoising autoencoder scRNA-seq deep learning
On-line přístup:	https://www.mdpi.com/2306-5354/12/8/829
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!