Document Type
Article
Publication Date
3-2022
Publication Title
Mammalian genome : official journal of the International Mammalian Genome Society
Keywords
JMG, Alleles, Animals, Databases, Genetic, Ecosystem, Gene Ontology, Genomics, Mice
JAX Source
Mamm Genome 2022 Mar; 33(1):4-18
Volume
33
Issue
1
First Page
4
Last Page
18
ISSN
1432-1777
PMID
34698891
DOI
https://doi.org/10.1007/s00335-021-09921-0
Grant
HG000330, HG10859, HD062499
Abstract
The Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI's mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of the Gene Ontology and Disease Ontology and uses these ontologies as standard terminologies for annotation. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are MGI's two major knowledgebases. Here, we highlight some of the recent changes and enhancements to MGD and GXD that have been implemented in response to changing needs of the biomedical research community and to improve the efficiency of expert curation. MGI can be accessed freely at http://www.informatics.jax.org .
Recommended Citation
Ringwald M,
Richardson J,
Baldarelli RM,
Blake JA,
Kadin JA,
Smith C,
Bult C.
Mouse Genome Informatics (MGI): latest news from MGD and GXD. Mamm Genome 2022 Mar; 33(1):4-18
Comments
We thank all the MGI curators and developers for their dedication and their many contributions to MGI. We are grateful to Dr. Hagit Shatkay (University of Delaware) and Dr. Xiangying Jiang (Amazon) for discussions about machine learning approaches to MGI’s literature curation processes.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.