BurnOmicsDB: A Curated and Standardized Database of Human Burn Injury Transcriptomics Across Tissues, Time Points, and Clinical Contexts

Public burn transcriptomic datasets remain difficult to compare because of differences in tissue source, study design, platform, annotation and statistical analysis. We developed BurnOmicsDB (https://peneapple.github.io/2026-BurnOmicsDB/), a curated and gene-centred web resource integrating six human burn-related Gene Expression Omnibus series comprising 1,013 public expression profiles. Dataset-specific quality control and differential-expression workflows were applied to 22 predefined contrasts across skin, wound margin, eschar, scar and blood, generating 448,735 standardized gene–contrast records. Gene identifiers and aliases were harmonized to support retrieval by official symbols, historical aliases, NCBI Gene IDs, Ensembl IDs and HGNC identifiers. Cross-tissue analysis showed that 564 of 1,444 genes with clear significant directions in both skin and blood exhibited opposite directions, highlighting the context dependence of burn-associated transcriptional responses. BurnOmicsDB enables code-free exploration and cross-study comparison of burn transcriptomic evidence for research and clinical reference, but is not intended for diagnosis or treatment decisions.