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Interpretable generative deep learning: an illustration with single cell gene expression data

Deep generative models can learn the underlying structure, such as pathways or gene programs, from omics data. We provide an introduction as well as an overview of such techniques, specifically illustrating their use with single-cell gene expression data. For example, the low dimensional latent repr...

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Detalles Bibliográficos
Autores principales: Treppner, Martin, Binder, Harald, Hess, Moritz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9360114/
https://www.ncbi.nlm.nih.gov/pubmed/34988661
http://dx.doi.org/10.1007/s00439-021-02417-6