Feature Genes for Sepsis Linked to Butyrate Metabolism and Oxidative Stress

Qinglu Fan published a dataset on figshare in April 2026. It contains results from a study identifying feature genes related to butyrate metabolism and oxidative stress in sepsis. The dataset likely includes machine learning-derived feature genes and validation results from cellular experiments and clinical samples.

Use Cases

• Validate diagnostic biomarkers for sepsis based on the identified feature genes ALDH1A1, CYP1B1, and GADD45A.
• Analyze associations between gene expression and immune cell infiltration based on the CIBERSORT analysis mentioned.
• Investigate the role of monocytes in sepsis pathogenesis based on the scRNA-seq analysis results.

Strengths

• The dataset is derived from multiple validation methods, including machine learning, cellular experiments, and clinical samples.
• It identifies three specific feature genes (ALDH1A1, CYP1B1, GADD45A) with diagnostic value.
• The study integrates analysis of immune cell infiltration, providing a multi-layered perspective.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is 131.5 KB, indicating a very limited scope of data.

Provenance

Source

figshare

Collection Method

Analysis of sepsis-related datasets using differential expression screening and machine learning algorithms.

Freshness

Last updated 2026-04-24 10:52:56; freshness should be verified.