Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues

Autoencoders have been used to model single-cell mRNA-sequencing data with the purpose of denoising, visualization, data simulation, and dimensionality reduction. We, and others, have shown that autoencoders can be explainable models and interpreted in terms of biology. Here, we show that such autoe...

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Detalhes bibliográficos

Principais autores:	Julie Sparholt Walbech, Savvas Kinalis, Ole Winther, Finn Cilius Nielsen, Frederik Otzen Bagger
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2021-12-01
coleção:	Cells
Assuntos:	autoencoders (AE) single-cell mRNA-sequencing data transfer learning deep learning artificial neural networks
Acesso em linha:	https://www.mdpi.com/2073-4409/11/1/85
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