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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التفاصيل البيبلوغرافية

الحاوية / القاعدة:	Bioengineering
المؤلفون الرئيسيون:	Wanlin Juan, Kwang Woo Ahn, Yi-Guang Chen, Chien-Wei Lin
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	MDPI AG 2025-07-01
الموضوعات:	dropout imputation autoencoder denoising autoencoder scRNA-seq deep learning
الوصول للمادة أونلاين:	https://www.mdpi.com/2306-5354/12/8/829