International Mammalian Genome Society

logo18th International Mouse Genome Conference

17-22 October 2004, Seattle, USA


Eppig JT, vandenBorre P, Lu I, Anagnostopoulos A, Burkart DL, Cassell MA, Dene H, Bello SM, Washburn LL, Lutz CM, Goldsmith CW, Smith CL

The Jackson Laboratory, Bar Harbor, United States

The major goal of model organism databases is to provide an integrated resource of biological and genomic information that supports knowledge discovery. The Mouse Genome Database ( provides this entrée into mouse as a model system. The genome sequence of mouse that underlies the species’ biology is fundamental and recently obtained, and will be a source of revision, reassembly, analyses and discovery for years to come. At the opposite end of the biological system spectrum, the phenotype, representing the manifestation of the “whole organism” genotype is by far more complex. To represent phenotypic information in a useful way, biologists must be able to approach the data from both a phenotype-centric or genotype-centric view. For example, ‘”what phenotypes are associated with mutations in this gene or in this genomic region?” or “In this genomic region what sequence changes affect heart development?” (genotype-centric) versus “What are the mouse models for Hermansky-Pudlak syndrome” or “ Which mice show insulin resistance and normal serum glucose?” (phenotype-centric). Representing these data robustly in MGD in ways that support variable knowledge resolution and integrate data with other biological information is challenging, but good initial steps in this direction are being developed. MGD is collaborating with RGD and Mouse Mutagenesis Centers on developing and annotating phenotypes using a shared structured vocabulary, the Mammalian Phenotype (MP) Ontology. MGD is expanding its phenotype data model and developing a new suite of user interfaces. These user interfaces take advantage of the MP ontology and allow users to query and view data from the genotype or phenotype perspectives. Progress on this work will be described as well as some of the remaining challenges.

Supported by NIH grants HG00330

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