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To serve the need for research across domains, the National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) team is developing and deploying a set of open source software tools that supports a comprehensive and reusable exploration and fusion of imaging, clinical, and molecular data. The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) projects have created a rich multi-domain data set. This data set, however, is in an infrastructure that provides limited query capability for identifying cases based on all of the available data types. (For example...?)

The CTIIP team will therefore develop a unified query interface to facilitate cross-disciplinary analysis. This infrastructure would then be applied to clinical/co-clinical settings, using data collected for this purpose, and provide a common platform and data engine for the hosting of “pilot challenges.” These pilot challenge projects will proactively facilitate biological and clinical research across three NCI divisions. The algorithms used in the pilot challenges will be shared with the community via an open-source software clearinghouse.

The approach taken to development in this project emphasizes modular semantic interoperability and open source tooling, making it immediately valuable to scientists with NCI funded research networks in the three research domains, as well as the national and international research communities, and providing a framework for enhanced adoption of these methods by biologists in the larger genomics/proteomic communities.

Most importantly, the common informatics infrastructure will provide researchers with analysis tools they can use to directly mine data from multiple highMost importantly, the common informatics infrastructure will provide researchers with analysis tools they can use to directly mine data from multiple high-volume information repositories, creating a foundation for research and decision support systems to better diagnose and treat patients with cancer.

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This is highly consistent with the research goals of the Informatics Imaging Working Group, the needs raised at the Imaging Informatics Workshop in March 2013, and the mission of CBIIT, and leverages critical resources and previous NCI investments to target important cancer problems, such as clinical decision support for predicting or assessment of response to therapy. All of these goals are consistent with the NCI BSA recommendations for CBIIT and the NCI focus on precision medicine.  The approach taken to development in this project emphasizes modular semantic interoperability and open source tooling, making it immediately valuable to scientists with NCI funded research networks in the three research domains, as well as the national and international research communities, and providing a framework for enhanced adoption of these methods by biologists in the larger genomics/proteomic communities.

Three separate sections with problem/solution for each aim. Status of the solution.

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