Supplementary Material 10 from a study identifying SEC14L5 as a potential biomarker for polycystic ovary syndrome (PCOS). The 1.8 MB CSV file, published on figshare by Zhe Wang under a CC-BY-4.0 license, likely contains results from integrated weighted gene co-expression network and machine learning analyses. The dataset was last updated on April 15, 2026.
Use Cases
- Validate the identified SEC14L5 biomarker in independent PCOS cohorts (inferred from domain, verify after download)
- Benchmark machine learning models for gene expression-based disease classification (inferred from domain, verify after download)
- Analyze gene co-expression network structures related to hormonal conditions (inferred from domain, verify after download)
Strengths
- Published on figshare with a clear CC-BY-4.0 license for open reuse.
- File size is 1.8 MB, indicating a manageable download and processing footprint.
- Last update timestamp is precise: 2026-04 15 03:31:38.
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's analysis pipeline.
Provenance
- Source
- Zhe Wang via figshare.
- Collection Method
- Likely generated as supplementary material from a computational biology study using gene co-expression network and machine learning analysis.
- Time Range
- null
- Freshness
- Last updated 2026-04-15 03:31:38.
- Geography
- null