Document Type
Article
Publication Date
1-6-2026
Original Citation
Smith CM,
Hayamizu TF,
Finger JH,
McCright IJ,
Xu J,
Campbell J,
Corbani LE,
Emerson J,
Frost PJ,
Liang H,
Richardson J,
Baldarelli RM,
Ringwald M.
The mouse Gene Expression Database (GXD): 2026 update. Nucleic Acids Res. 2026;54(D1):D1190–D6.
Keywords
JMG, JGM, Animals, Mice, Databases, Genetic, Gene Expression Profiling, Transcriptome, Software, RNA-Seq, Gene Expression
JAX Source
Nucleic Acids Res. 2026;54(D1):D1190–D6.
ISSN
1362-4962
PMID
41261740
DOI
https://doi.org/10.1093/nar/gkaf1236
Grant
This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Develop- ment (NICHD) of the National Institutes of Health (NIH) [HD062499]. Funding to pay the Open Access publication charges for this article was provided by NIH [HD062499].
Abstract
The Gene Expression Database (GXD; https://www.informatics.jax.org/expression.shtml) is an extensive, well-curated community resource that provides detailed information about gene expression patterns in mouse strains and mutants, with a particular emphasis on development. For over 25 years, GXD has systematically curated the scientific literature and collaborated with large-scale expression projects to compile and integrate detailed expression data from multiple assay types, including RNA in situ hybridization, immunohistochemistry, in situ reporter (knock-in), RT-PCR, northern blot, and western blot experiments. In recent years, GXD has expanded its scope to include bulk RNA-Seq data, imported from the EMBL-EBI Expression Atlas. Since our last report in 2021, we continued to add data to GXD on a daily basis, and we implemented new search and display features. These include: (i) searches for qualitative differential gene expression and expression profiles that include both classical types of expression data and RNA-Seq data; (ii) browsing, searching, and filtering for cell-type-specific gene expression information; and (iii) an enhancement of our RNA-Seq and microarray experiment metadata index and search to allow users to quickly and reliably find bulk, single-cell, or spatial RNA-Seq data in the public repositories.