scGNN: a novel graph neural network framework for single-cell RNA-Seq analyses
Published in bioRxiv (Cold Spring Harbor Laboratory), 2020
ABSTRACT Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differential patterns in gene expression. We introduce the s…
Recommended citation: Juexin Wang, Anjun Ma, Yuzhou Chang, Jianting Gong, Yuexu Jiang, Hongjun Fu, Cankun Wang, Ren Qi, et al.. (2020). "scGNN: a novel graph neural network framework for single-cell RNA-Seq analyses" bioRxiv (Cold Spring Harbor Laboratory).
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