Data Sheet 4_Transcriptomic and experimental identification of immune- and telomere-relate

864 differentially expressed genes, including 833 upregulated and 31 downregulated, were identified from public-database transcriptome data. The dataset results from a study by Rong Ma, posted on figshare, that used differential expression analysis and machine learning to identify key biomarkers CCNL1 and NAMPT. The data was last updated on 2026-05-22.

Use Cases

• Validate diagnostic biomarkers for pelvic organ prolapse based on identified key genes CCNL1 and NAMPT.
• Explore molecular regulatory networks based on the predicted 21 key nodes and 28 interactions.
• Predict potential therapeutic compounds based on the 14 drug candidates identified in the study.
• Perform pathway enrichment analysis based on results such as ubiquitin-mediated proteolysis from GSEA.

Strengths

• Identifies 864 differentially expressed genes with specific counts of up- and down-regulated entries.
• Key biomarkers CCNL1 and NAMPT were validated by RT-qPCR with a reported p-value < 0.05.
• The associated nomogram model achieved an AUC of 0.847 for diagnostic potential.
• Analysis includes predicted interactions with 21 key nodes and 28 interactions in a molecular network.

Limitations

• The dataset is extremely small at 393.0 B, indicating limited raw data or a summary file.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analysis.

Provenance

Source

figshare, author Rong Ma.

Collection Method

Analysis of public-database transcriptome data using differential expression analysis, immune infiltration, WGCNA, and machine learning.

Freshness

Last updated 2026-05-22 06:10:45; freshness should be verified.