GO Enrichment Analysis Results for Idiopathic Pulmonary Fibrosis Biomarker Genes

A 28.4 KB Excel file containing results from a multi-omics and machine-learning study of idiopathic pulmonary fibrosis (IPF). The dataset, authored by Yongbin Wang and last updated in April 2026, presents gene ontology enrichment analysis for candidate biomarkers identified through integrated transcriptomic data and 101 machine-learning model combinations.

Use Cases

• Validate candidate biomarkers (CD247, IL7R, RETN) for idiopathic pulmonary fibrosis based on the multi-omics integration described.
• Replicate functional enrichment analyses on spliceosome-related pathways as indicated in the study results.
• Build diagnostic models using the three identified genes, as suggested by the reported artificial neural network performance.
• Investigate regulatory networks involving transcription factors and non-coding RNAs like circRNA CDR1as, as highlighted in the analysis.

Strengths

• Results are derived from an integrated analysis of bulk transcriptomic, single-cell RNA sequencing, and literature-derived gene sets.
• Candidate genes were validated using an independent clinical cohort with RT-qPCR, as stated in the methods.
• The analysis employed 101 machine-learning model combinations, including random forest, LASSO, and support vector machine.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (28.4 KB), indicating limited scope, likely containing summary results rather than raw data.

Provenance

Source

Analysis integrated data from the Gene Expression Omnibus (GEO) and other public sources.

Collection Method

Candidate genes identified through differential expression analysis, consensus clustering, and machine-learning feature selection.

Time Range

Temporal coverage of the underlying data is not specified.

Freshness

Last updated 2026-04-23 17:24:14; freshness should be verified.

Geography

Spatial coverage is not specified.