Jan 2, 2023 · Here, we demonstrate that scGMAAE has good scalability and can process large-scale scRNA-seq data. Compared with some popular single-cell ...
scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data · Abstract · Publication types · MeSH terms.
scGMAAE: Gaussian mixture adversarial autoencoders for ...
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Jan 3, 2024 · scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data. January 2023; Briefings in Bioinformatics ...
Jan 1, 2023 · scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data. ... scRNA-seq data, which are widely ...
Jan 30, 2024 · Here, we propose a deep neural generative framework, the dynamic batching adversarial autoencoder. (DB-AAE), which excels at denoising scRNA-seq ...
scGMAAE: Gaussian Mixture Adversarial Autoencoder for scRNA-seq Data. All source codes are in code.rar, and you can run scGMAAE with run_scGMAAE.py. Here, we ...
Jan 3, 2024 · scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data. Brief Bioinform. 2023; 24bbac585. View in ...
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Apr 21, 2023 · In this study, we propose an improved variational autoencoder model (termed DREAM) for dimensionality reduction and a visual analysis of scRNA- ...
However, the small proportion of rare cells in scRNA-seq data ... scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq ...
scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data ... diversification analysis of scRNA-seq data. Citing ...