Sample clustering and subtyping analysis.

<p>A unsupervised cluster typing based on the above 21 differential genes showed that type 2 was the best. B shows the differential expression of 21 differential genes among different types, ns p > 0.05,*p < 0.05,**p < 0.01,***p < 0.001; C Heat map shows the relationship between cl...

Full description

Saved in:

Bibliographic Details
Main Author:	Ziyang Liu (242055) (author)
Other Authors:	Zengyuan Qin (22075816) (author), Wenxin Bai (8362707) (author), Shasha Wang (346796) (author), Chunling Huang (551460) (author), Na Li (6550) (author), Lei Yan (69509) (author), Yue Gu (422614) (author), Fengmin Shao (629829) (author)
Published:	2025
Subjects:	Microbiology Cell Biology Genetics Molecular Biology Biotechnology Immunology Marine Biology Cancer Infectious Diseases Virology Biological Sciences not elsewhere classified Information Systems not elsewhere classified severe global complication including feature selection immunohistochemical results confirmed gene expression changes explicit sample sizes differential pathway activation normal kidney tissues machine learning approaches machine learning algorithms immune infiltration patterns identifying diagnostic biomarkers dkd tissues compared differentially expressed glycosylation define molecular subtypes six hub genes machine learning molecular subtypes immune infiltration diagnostic biomarkers hub genes normal samples related genes xlink "> unsupervised clustering study aimed roc curves qpcr validation protein glycosylation personalized therapies neutrophil activity larger cohorts key player integrating bioinformatics future studies functional enrichment disease heterogeneity clinical dkd
Tags:	Add Tag No Tags, Be the first to tag this record!

Sample clustering and subtyping analysis.

Similar Items