SEC14L5 Biomarker Data for Polycystic Ovary Syndrome Analysis

Supplementary Material 9 from a study titled 'Integrated weighted gene co-expression network analysis and machine learning analysis identifies SEC14L5 as a potential biomarker for polycystic ovary syndrome'. The dataset is a 53.6 KB CSV file published on figshare by Zhe Wang under a CC-BY-4.0 license. It was last updated on 2026-04-15.

Use Cases

• Validate the SEC14L5 gene as a biomarker for polycystic ovary syndrome (inferred from domain, verify after download)
• Reproduce the integrated gene co-expression and machine learning analysis pipeline (inferred from domain, verify after download)
• Use as a supplementary feature set for training diagnostic classification models (inferred from domain, verify after download)

Strengths

• Published on figshare with a permissive CC-BY-4.0 license.
• File size is 53.6 KB, indicating a focused and manageable dataset.
• Last updated date is explicitly recorded as 2026-04-15.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count and column definitions are unknown, which may limit suitability assessment.
• Data may reflect the specific methodological bias of the source study.

Provenance

Source

Zhe Wang via figshare.

Collection Method

Likely generated as supplementary material from computational biology analysis.

Time Range

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Freshness

Last updated 2026-04-15 03:31:38; freshness should be verified.

Geography

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