469 and 153 differentially expressed genes (DEGs) were screened from mouse lung tissue datasets GSE244335 and GSE216943, respectively, with 94 overlapping genes. The dataset, created by Lingfeng Chen and last updated on 2026-05-22, contains results from bioinformatic analyses including Gene Ontology, KEGG pathway, and protein-protein interaction network construction. It aims to identify key genes and shared pathogenic pathways associated with acute pancreatitis-associated acute lung injury.
Use Cases
- Identify hub genes implicated in inflammatory pathways based on the protein-protein interaction network analysis described.
- Perform cross-species comparison of systemic inflammatory responses based on the common GO-BP terms identified between mouse and human data.
- Validate candidate molecular signatures like the IL-17/NF-κB signaling pathway based on the computational findings generated.
- Screen for potential diagnostic or therapeutic targets for AP-ALI based on the identified differentially expressed genes.
Strengths
- Includes results from multiple datasets (GSE244335, GSE216943, GSE194331) enabling cross-species and cross-tissue comparison.
- Analysis identified 94 common DEGs and specific hub genes (e.g., IL-1β, CCL3) providing concrete molecular targets.
- Released under a permissive CC-BY-4.0 license, facilitating reuse and redistribution.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment for certain analytical tasks.
- The dataset is small at 2.1 MB, which may limit the complexity of analyses it directly supports.
Provenance
- Source
- Gene Expression Omnibus (GEO) database.
- Collection Method
- Bioinformatics analysis of retrieved gene expression datasets, including differential expression screening, GO/KEGG enrichment, and PPI network construction.
- Time Range
- null
- Freshness
- Last updated 2026-05-22 17:41:23; freshness should be verified.
- Geography
- null