PGD, MAPK14, and KRAS Biomarkers for Neonatal Sepsis Diagnosis

Li Luo's dataset contains computational results identifying PGD, MAPK14, and KRAS as diagnostic biomarkers for neonatal sepsis. The data was generated from transcriptomic analysis of patient samples (GSE69686, GSE25504) using machine learning and bioinformatics methods. It was last updated on 2026-05-29.

Use Cases

• Validate diagnostic biomarkers for neonatal sepsis based on identified genes PGD, MAPK14, and KRAS.
• Investigate immune cell infiltration patterns in sepsis based on the described CIBERSORT analysis.
• Screen FDA-approved drugs for potential repurposing based on molecular docking results against MAPK14 and KRAS.
• Study the role of ferroptosis and cuproptosis pathways in neonatal sepsis pathogenesis.

Strengths

• Identifies three specific biomarkers (PGD, MAPK14, KRAS) validated by multiple machine learning models.
• External validation reported strong diagnostic performance with AUC > 0.79.
• Includes in vitro experimental validation using LPS-stimulated THP-1-derived macrophages.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is contained in a 1.4 MB DOCX file, which may require extraction of structured data.

Provenance

Source

figshare, author Li Luo.

Collection Method

Transcriptomic data analysis from GEO datasets GSE69686 and GSE25504, using differential expression, WGCNA, PPI networks, and machine learning (LASSO, SVM-RFE, XGBoost).

Freshness

Last updated 2026-05-29 06:15:06; freshness should be verified.