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As discussed so far, cancer research is needed across domains. To serve this need, the National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) team has set a goal of plans to meet it by creating a data mashup interface that accesses The Cancer Genome Atlas (TCGA) clinical and molecular data, The Cancer Imaging Archive (TCIA) in-vivo imaging data, caMicroscope pathology data, a pilot data set of animal model data, and relevant imaging annotation and markup data.

The TCGA project is producing a comprehensive genomic characterization and analysis of 200 types of cancer and providing this information to the research community. TCIA and the underlying National Biomedical Image Archive (NBIA) manage well-curated, publicly-available collections of medical image data. The linkages between TCGA and TCIA are valuable to researchers who want to study diagnostic images associated with the tissue samples sequenced by TCGA..

Although TCGA and TCIA comprise a rich, multi-domain data set, they are in an infrastructure that provides limited query capability. Researchers want to query both databases together to identify cases based on all available data types. Moreover, without common data standards, it's even more difficult impossible to integrate these data from other domains such as sets with those from digital pathology and animal models, due to a lack of common data standardsco-clinical/small animal model environments.

To address these limitations, the CTIIP team is developing a unified query interface to make it easier to analyze data from different research domains. This interface, plus related open-source software and data standards, would then be applied to co-clinical, small animal model data, and provide a common platform and data engine for the hosting of “pilot challenges.” These pilot challenges will proactively facilitate biological and clinical research across the clinical, pre-clinical, and digital pathology imaging research domains.

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