Overview of the ZINB-GRAN: Starting with the count matrix from scRNA-seq data as input, ZINB-GRAN first constructs a WGCN from gene expression data. Based on this WGCN, it builds an initial regulatory ...
Abstract: With the powerful learning ability of deep convolutional networks, deep clustering methods can extract the most discriminative information from individual data and produce more satisfactory ...
Abstract: Existing deep embedding clustering methods fail to sufficiently utilize the available off-the-shelf information from feature embeddings and cluster assignments, limiting their performance.
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