Toward fully integrated mouse phenotype data

The multitude of murine genetic resources available worldwide, including inbred mouse lines, spontaneous and induced mutants, and ES lines ready for conditional gene targeting, represent a unique resource for the biomedical community. Recent international efforts are striving to complete the functional annotation the mouse genome, which will allow a systems-based view of mammalian biological networks and causes of disease. For this purpose, integration of the broad range of phenotype data has presented new challenges. The OBO ontologies and Minimum Information Standards have provided important frameworks for the integration and sharing of phenotype information. On the other hand, extension of these tools will need to allow advanced integration of phenotype data, namely, fully machine-processable integration of quantitative and qualitative data, advanced classification of phenotypes, and representation of the relationships between mouse phenotypes and human diseases. We propose that integration based on top-level ontology using YATO is a sophisticated answer to this issue.