Common gene signatures in pSS dataset (GSE84844) and IIP dataset (GSE32537) datasets using WGCNA algorithm.

<p>(A) Determination of optimal soft-thresholding power for pSS analysis. (B) Dendrogram of co-expressed gene clusters identified in pSS datasets. (C) Module-trait association heatmap generated for pSS cohorts. (D) Scatter plot visualization of gene significance-module membership correlations...

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Bibliographic Details
Main Author:	Jingqi Dong (22378904) (author)
Other Authors:	Zelin Wang (3930725) (author), Yanan Xu (678670) (author), Shufen Liang (20577294) (author)
Published:	2025
Subjects:	Biochemistry Cell Biology Genetics Molecular Biology Pharmacology Immunology Cancer Infectious Diseases Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified significant pathophysiological divergence reliable shared biomarkers regulatory network construction molecular dynamics simulations molecular docking coupled interstitial lung disease improving clinical outcomes identify shared biomarkers gren &# 8217 frequently delayed due exploration common biomarkers weighted gene co tf )- gene identify gene modules gene expression omnibus differential expression gene identify candidate biomarkers ctd 00003205 ). resting nk cells potential therapeutic agent promote disease progression machine learning approaches discovery holds promise expression network analysis memory b cells machine learning gene interactions siglec10 expression candidate genes potential coregulators diagnostic potential xlink "> validation cohorts transcription factor target prediction target organs study revealed siglec10 ), pathogenic mechanisms oocyte maturation metabolic regulation may affect inflammatory disorder ild ). hub genes hindered elucidation genes obtained enrichment analysis diagnostic challenge derived genes
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Common gene signatures in pSS dataset (GSE84844) and IIP dataset (GSE32537) datasets using WGCNA algorithm.

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