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Similarity-assisted variational autoencoder for nonlinear dimension reduction with application to single-cell RNA sequencing data
BACKGROUND: Deep generative models naturally become nonlinear dimension reduction tools to visualize large-scale datasets such as single-cell RNA sequencing datasets for revealing latent grouping patterns or identifying outliers. The variational autoencoder (VAE) is a popular deep generative method...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647110/ https://www.ncbi.nlm.nih.gov/pubmed/37964243 http://dx.doi.org/10.1186/s12859-023-05552-1 |