The H5N1 virus may now be well established in different Southeast Asian countries. Despite the implementation of control measures, it is probable that these countries will continue to face new outbreaks in poultry. The conditions under which the virus maintains itself in the environment are not well known. It is difficult to prevent virus re-emergence in possible local persistence spots, or the periodic reintroduction of the virus [25] . Controlling the disease within the poultry population is a critical issue for both the public health and agricultural economic systems. The restructuring of poultry production from open-housed to closed systems has started in Thailand but the process will take time and considerable cooperative effort. Therefore, to limit the number and size of future outbreaks in the poultry population, the focus of efforts should be on controlling the movement of both live poultry and avian products. Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information BACKGROUND: The genetic contributions to human common disorders and mouse genetic models of disease are complex and often overlapping. In common human diseases, unlike classical Mendelian disorders, genetic factors generally have small effect sizes, are multifactorial, and are highly pleiotropic. Likewise, mouse genetic models of disease often have pleiotropic and overlapping phenotypes. Moreover, phenotypic descriptions in the literature in both human and mouse are often poorly characterized and difficult to compare directly. METHODS: In this report, human genetic association results from the literature are summarized with regard to replication, disease phenotype, and gene specific results; and organized in the context of a systematic disease ontology. Similarly summarized mouse genetic disease models are organized within the Mammalian Phenotype ontology. Human and mouse disease and phenotype based gene sets are identified. These disease gene sets are then compared individually and in large groups through dendrogram analysis and hierarchical clustering analysis. RESULTS: Human disease and mouse phenotype gene sets are shown to group into disease and phenotypically relevant groups at both a coarse and fine level based on gene sharing. CONCLUSION: This analysis provides a systematic and global perspective on the genetics of common human disease as compared to itself and in the context of mouse genetic models of disease. Common complex diseases such as cardiovascular disease, cancer, and autoimmune disorders; metabolic conditions such as diabetes and obesity, as well as neurological and psychiatric disorders make up a majority of health morbidity and mortality in developed countries. The specific genetic contributions to disease etiology and relationships to environmental factors in common disorders are unclear; complicated by many factors such as gene-gene interactions, the balance between susceptibility and protective alleles, copy number variation, low relative risk contributed by each gene, and a myriad of complex environmental inputs.