Scmaskgan: masked multi-scale CNN and attention-enhanced GAN for scRNA-seq dropout imputation
Abstract Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity, but dropout events, where gene expression is undetected in individual cells, present a significant challenge. We propose scMASKGAN, which transforms matrix imputation into a pixel restoration...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-025-06138-9 |
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