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This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.
The Growing Up Today Study is a collaborative study between clinicians, researchers, and thousands of participants across the US and beyond. The aim of this study is to gain a deeper understanding of the factors that affect health throughout life. Together we are working to building one of the most powerful resources for fighting cancer, obesity, heart disease, depression, and so much more.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH) is a centralized resource that allows researchers to share and access de-identified data from studies funded by NICHD. DASH also serves as a portal for requesting biospecimens from selected DASH studies.
BEI Resources was established by the National Institute of Allergy and Infectious Diseases (NIAID) to provide reagents, tools and information for studying Category A, B, and C priority pathogens, emerging infectious disease agents, non-pathogenic microbes and other microbiological materials of relevance to the research community. BEI Resources acquires authenticates, and produces reagents that scientists need to carry out basic research and develop improved diagnostic tests, vaccines, and therapies. By centralizing these functions within BEI Resources, access to and use of these materials in the scientific community is monitored and quality control of the reagents is assured
PhysioBank is a large and growing archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials