SEC14L5 Biomarker Data for Polycystic Ovary Syndrome

Supplementary Material 8 from a study integrating weighted gene co-expression network analysis and machine learning. The 4.2 KB CSV file, published on figshare by Zhe Wang in April 2026, likely contains results identifying SEC14L5 as a potential biomarker for polycystic ovary syndrome. Its small size suggests it is a focused output table rather than a raw data repository.

Use Cases

• Validate SEC14L5 as a biomarker using independent cohorts (inferred from domain, verify after download)
• Benchmark gene selection algorithms for complex traits (inferred from domain, verify after download)
• Reproduce network analysis results from the parent study (inferred from domain, verify after download)

Strengths

• Published on figshare under a CC-BY-4.0 license, enabling open reuse.
• File size is precisely 4.2 KB, indicating a compact, focused dataset.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count and column definitions are unknown, limiting suitability assessment.
• Data may reflect methodological bias inherent to the specific parent study.

Provenance

Source

Zhe Wang via figshare.

Collection Method

Likely generated as supplementary output from integrated weighted gene co-expression network and machine learning analysis.

Time Range

null

Freshness

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

Geography

null