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Found 24 result(s)
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
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.
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
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
BioLINCC is the Biologic Specimen and Data Repository Coordinating Center. The center coordinates data and biospecimens from NHLBI-funded studies that are available for use in other approved studies. The center also creates teaching data sets from NHLBI-funded studies for use in training future biostatisticians.
The Comprehensive Epidemiologic Data Resource (CEDR) is the U.S. Department of Energy (DOE) electronic database comprised of health studies of DOE contract workers and environmental studies of areas surrounding DOE facilities. DOE recognizes the benefits of data sharing and supports the public's right to know about worker and community health risks. CEDR provides independent researchers and educators with access to de-identified data collected since the Department's early production years. Current CEDR holdings include more than 76 studies of over 1 million workers at 31 DOE sites. Access to these data is at no cost to the user.
The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) is an information system designed to support research on bacterial and viral infectious diseases. BV-BRC combines two long-running BRCs: PATRIC, the bacterial system, and IRD/ViPR, the viral systems.
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.
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The Centre for Clinical Trials Cologne (Köln ZKS) aims to support all processes of clinical trials and the quality of patient-oriented clinical research in an academic environment. It supports doctors of University Hospital of Cologne, other clinics, study groups and professional associations in the design and conduct of clinical trials. For the pharmaceutical industry and contract research organizations, the ZKS Köln is a clinic near partner for medical research projects.
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
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Human biomaterial banks (short: biobanks) are collections of human body substances (i.e. blood, DNA, urine or tissue) connected with disease specific information. This allow for research of relations between deseases and underlying (molecular) modifications and paves the way for developing target-oriented therapies ("personalized medicine"). The biobank material arises from samples taken for therapeutical or diagnostic reasons or is extracted in the context of clinical trials. An approval for usage by the patient is always needed prior to any research activities.
The WorldWide Antimalarial Resistance Network (WWARN) is a collaborative platform generating innovative resources and reliable evidence to inform the malaria community on the factors affecting the efficacy of antimalarial medicines. Access to data is provided through diverse Tools and Resources: WWARN Explorer, Molecular Surveyor K13 Methodology, Molecular Surveyor pfmdr1 & pfcrt, Molecular Surveyor dhfr & dhps.
The N3C Data Enclave is a secure portal containing a very large and extensive set of harmonized COVID-19 clinical electronic health record (EHR) data. The data can be accessed through a secure cloud Enclave hosted by NCATS and cannot be downloaded due to regulatory control. Broad access is available to investigators at institutions that sign a Data Use Agreements and via Data Use Requests by investigators. The N3C is a unique open, reproducible, transparent, collaborative team science initiative to leverage sensitive clinical data to expedite COVID-19 discoveries and improve health outcomes.
diversitydata.org is an online tool for exploring quality of life data across metropolitan areas for people of different racial/ethnic groups in the United States. It provides values and rankings for the largest U.S. metropolitan areas on different indicators in 8 areas of life (domains), including demographics, education, economic opportunity, housing, neighborhoods, and health. It also provides a simple mapping utility, showing the range of indicator values for metros across the U.S. Data from 1999 indicators is archives in the companion Diversity Data Archive (https://diversitydata-archive.org/). For a wider selection of data on child wellbeing, visit our partner site, diversitydatakids.org (https://www.diversitydatakids.org/). diversitydata.org has been named a Health Data All Star by the Health Data Consortium. The list was compiled in consultation with leading health researchers, government officials, entrepreneurs, advocates and others to identify the health data resources that matter most.
<<<!!!<<< USHIK was archived because some of the metadata are maintained by other sites and there is no need for duplication. The USHIK metadata registry was a neutral repository of metadata from an authoritative source used to promote interoperability and reuse of data. The registry did not attempt to change the metadata content but rather provided a structured way to view data for the technical or casual user. Complete information see: https://www.ahrq.gov/data/ushik.html >>>!!!>>>
The Social Science Data Archive is still active and maintained as part of the UCLA Library Data Science Center. SSDA Dataverse is one of the archiving opportunities of SSDA, the others are: Data can be archived by SSDA itself or by ICPSR or by UCLA Library or by California Digital Library. The Social Science Data Archives serves the UCLA campus as an archive of faculty and graduate student survey research. We provide long term storage of data files and documentation. We ensure that the data are useable in the future by migrating files to new operating systems. We follow government standards and archival best practices. The mission of the Social Science Data Archive has been and continues to be to provide a foundation for social science research with faculty support throughout an entire research project involving original data collection or the reuse of publicly available studies. Data Archive staff and researchers work as partners throughout all stages of the research process, beginning when a hypothesis or area of study is being developed, during grant and funding activities, while data collection and/or analysis is ongoing, and finally in long term preservation of research results. Our role is to provide a collaborative environment where the focus is on understanding the nature and scope of research approach and management of research output throughout the entire life cycle of the project. Instructional support, especially support that links research with instruction is also a mainstay of operations.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
FORS is the Swiss Centre of Expertise in the Social Sciences. FORS maintains a national digital archive for social science research data, implements large-scale national and international surveys, offers data and research information services to researchers and academic institutions, and conducts methodological and thematic research. FORS Data Service is FORS’ resource centre for research and teaching in the social sciences. It provides data management support and training, and it archives, disseminates and promotes quantitative and qualitative data. The Data Service maintains a comprehensive and up-to-date inventory of social science research projects in Switzerland, and makes available a wide range of datasets for secondary analysis. Databases at the FORS Data Service are: SWISSUbase and DeVisu (for variable level metadata for important surveys).