Data Sheet 7_Transcriptomic and experimental identification of immune- and telomere-relate

Data Sheet 7 from a study by Rong Ma, uploaded to figshare on 2026-05-22, contains transcriptomic data related to pelvic organ prolapse (POP). The underlying research identified 864 differentially expressed genes and used machine learning to pinpoint CCNL1 and NAMPT as key biomarkers. The dataset is associated with a CC-BY-4.0 license.

Use Cases

• Validating the diagnostic potential of CCNL1 and NAMPT biomarkers based on the reported ROC analysis.
• Exploring gene regulatory networks based on the predicted interactions with 21 key nodes and 28 interactions.
• Identifying potential therapeutic compounds based on the 14 drug candidates predicted in the study.
• Conducting pathway enrichment analysis based on the ubiquitin-mediated proteolysis and other pathways identified via GSEA.

Strengths

• Dataset is associated with a specific, peer-reviewed research methodology including differential expression analysis of 864 genes and machine learning validation.
• Key findings, including two identified biomarkers (CCNL1 and NAMPT), were validated by RT-qPCR, suggesting an experimental basis.
• The dataset is published under a permissive CC-BY-4.0 license, facilitating reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (446.0 B), indicating it likely contains summary or identifier lists rather than raw transcriptomic data.

Provenance

Source

Rong Ma via figshare.

Collection Method

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

Freshness

Last updated 2026-05-22 06:10:47; freshness should be verified.