Multidisciplinary approaches are being utilized by the investigators of the Northern New England Clinical and Translational Research Network (NNE-CTR) to advance translational medicine for health problems endemic in the aging, rural populations of northern New England, including cancer, cardiovascular disease and substance abuse. These approaches are heavily dependent on bioinformatics, biomedical and clinical informatics, data mining of electronic health records, large data management, high throughput genomic analyses, delivery of integrated clinical, research and administrative data, and study design and statistical analysis support for clinical and epidemiologic investigators. The goal of the Clinical Research Design, Epidemiology, and Biostatistics Core (CRDEB) is to support and educate NNE-CTR Cores and investigators in the appropriate use of these computationally-intensive approaches and technologies in their studies. Accordingly, the CRDEB Core will provide the following types of support to participating investigators and their collaborators: 1) Support for research navigation, study design and statistical analyses for epidemiologic, clinical and translational studies will utilize a Clinical and Translational Research Catalyst model that has been successfully used to foster T1 and T2 translational research at Maine Medical Center (MMC) to engage new clinical and basic investigators in translational research. This Core will also support a Practice-based Research Catalyst who will facilitate T3 and T4 research with clinicians in the Rural Health Research and Delivery Core; 2) Support for genomic analyses, including data management and analysis of high-throughput genotyping and next generation sequencing data, as well as data mining of publicly available genomics resources, will take advantage of the extensive computing resources and bioinformatics specialists in the molecular Bioinformatics Shared Resource at the University of Vermont (UVM); 3) Support for computer program, plug-in, and applications development for biomedical informatics and clinical informatics analyses, mining electronic health records, and querying public genomic and other research and administrative data sources will be provided. The enablement of contemporary biomedical research increasingly requires the development of new approaches for organizing, analyzing and retrieving data from a plethora of sources and transforming them into knowledge that can support research endeavors. Biomedical informatics is the trans-disciplinary science that is specifically focused on the development, deployment, and evaluation of such techniques. We will extend the methods and tools for delivering integrated clinical, research and administrative data that have been developed by the Biomedical Informatics Unit at UVM, as well as the Observational Health Data Sciences and Informatics collaborative and its common data model, currently in use at MMC, to all NNE-CTR investigators.
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