Repository of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors, and the the ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in the context of genetic and genomic data, using semantics and statistics. The discovery system provides basic and clinical science researchers, informaticists, and medical professionals with an integrated interface and set of discovery tools to reveal the genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. The aim for this system is to promote true translational research, in that clinicians can connect with model systems researchers with expertise in related phenotypes, assays, or models. In addition to providing easy-to-use tools to navigate the model-disease data landscape, it also provides services for other resources, and educational outreach regarding the production of structured data for biomedical discovery. Model systems are the cornerstone of biomedical research to investigate biological processes, test gene-based disease hypotheses, and develop and test disease treatments. The vast knowledge about model systems can be better utilized if semantically aggregated and made queryable based on any number of facets, such as phenotypic similarity, network analysis, gene expression and function, and genomics.

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