Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.The accelerating availability of molecular sequences, particularly the sequences of entire genomes, has transformed both the theory and practice of experimental biology. Where once biochemists characterized proteins by their diverse activities and abundances, and geneticists characterized genes by the phenotypes of their mutations, all biologists now acknowledge that there is likely to be a single limited universe of genes and proteins, many of which are conserved in most or all living cells. This recognition has fuelled a grand unification of biology; the information about the shared genes and proteins contributes to our understanding of all the diverse organisms that share them. Knowledge of the biological role of such a shared protein in one organism can certainly illuminate, and often provide strong inference of, its role in other organisms.Progress in the way that biologists describe and conceptualize the shared biological elements has not kept pace with sequencing. For the most part, the current systems of nomenclature for genes and their products remain divergent even when the experts appreciate the underlying similarities. Interoperability of genomic databases is limited by this lack of progress, and it is this major obstacle that the Gene Ontology (GO) Consortium was formed to address.

The mouse is a prime organism of choice for modelling human disease. Over 450 inbred strains of mice have been described, providing a wealth of different genotypes and phenotypes for genetic and other studies. As new strains are generated and others become extinct, it is useful to review periodically what strains are available and how they are related to each other, particularly in the light of available DNA polymorphism data from microsatellite and other markers. We describe the origins and relationships of inbred mouse strains, 90 years after the generation of the first inbred strain. Given the large collection of inbred strains available, and that published information on these strains is incomplete, we propose that all genealogical and genetic data on inbred strains be submitted to a common electronic database to ensure this valuable information resource is preserved and used efficiently.

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.