SEC14L5 Biomarker Data for Polycystic Ovary Syndrome Analysis

Supplementary Material 11 from a study integrating weighted gene co-expression network analysis and machine learning to identify SEC14L5 as a potential biomarker for polycystic ovary syndrome. The 6.6 KB text file was published by Zhe Wang on figshare under a CC-BY-4.0 license and last updated on 2026-04-15.

Use Cases

• Validate SEC14L5 as a biomarker candidate in independent cohorts (inferred from domain, verify after download)
• Reproduce the integrated network and machine learning analysis pipeline (inferred from domain, verify after download)
• Use as supplementary data for meta-analyses on polycystic ovary syndrome (inferred from domain, verify after download)

Strengths

• Published on figshare with a CC-BY-4.0 license, facilitating open reuse.
• Last updated on 2026-04-15 03:31:38, indicating recent maintenance.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count and column structure are unknown, limiting suitability assessment.
• The 6.6 KB size suggests a very limited scope, likely containing only specific supplementary results.

Provenance

Source

figshare, authored by Zhe Wang.

Collection Method

Likely generated as supplementary material for a research publication.

Time Range

null

Freshness

Last updated 2026-04-15 03:31:38.

Geography

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