The Mouse Genome Database (MGD): mouse biology and model systems

TLDR

The Mouse Genome Database (MGD) integrates genetic, genomic, and phenotypic data on the laboratory mouse, a key model for human biology and disease. MGD offers a data‑mining platform to generate translational research hypotheses through comparative genotype, phenotype, and functional analyses. MGD aggregates gene, phenotype, DNA, and protein data from literature curation, investigator submissions, and resources such as Ensembl, UniProt, and NCBI, normalizes genome and variant information, integrates comparative mammalian data, collaborates on ontologies like GO and MP, and provides web‑based and computational access. Recent updates include linking gene‑trap data to mouse genes and adding a batch query feature for customized data retrieval.

Abstract

The Mouse Genome Database, (MGD, http://www.informatics.jax.org /), integrates genetic, genomic and phenotypic information about the laboratory mouse, a primary animal model for studying human biology and disease. MGD data content includes comprehensive characterization of genes and their functions, standardized descriptions of mouse phenotypes, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information including comparative data on mammalian genes. Data within MGD are obtained from diverse sources including manual curation of the biomedical literature, direct contributions from individual investigator's laboratories and major informatics resource centers such as Ensembl, UniProt and NCBI. MGD collaborates with the bioinformatics community on the development of data and semantic standards such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology. MGD provides a data-mining platform that enables the development of translational research hypotheses based on comparative genotype, phenotype and functional analyses. Both web-based querying and computational access to data are provided. Recent improvements in MGD described here include the association of gene trap data with mouse genes and a new batch query capability for customized data access and retrieval.