DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering

Abstract Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic technique that is utilized to investigate single-cell transcriptomes. Cluster analysis can effectively reveal the heterogeneity and diversity of cells in scRNA-seq data, but existing clustering algorithms strug...

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Autors principals:	Qingyun Gao, Qing Ai
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2024-06-01
Col·lecció:	Scientific Reports
Matèries:	ScRNA-seq data Deep clustering Extreme learning machine Dual correlation information reduction Feature fusion
Accés en línia:	https://doi.org/10.1038/s41598-024-64217-y
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