scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

Single-cell RNA-Seq suffers from heterogeneity in sequencing sparsity and complex differential patterns in gene expression. Here, the authors introduce a graph neural network based on a hypothesis-free deep learning framework as an effective representation of gene expression and cell–cell relationsh...

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Autores principales: Juexin Wang, Anjun Ma, Yuzhou Chang, Jianting Gong, Yuexu Jiang, Ren Qi, Cankun Wang, Hongjun Fu, Qin Ma, Dong Xu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Science
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Acceso en línea:https://doaj.org/article/a461a5e31f27497ea7c1e605964bab0a
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