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Found 20 result(s)
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimerā€™s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimerā€™s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimerā€™s disease patients, mild cognitive impairment subjects, and elderly controls. "
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.
The National Health Research and Studies Portal (NHRSP) is an initiative to build a national digital research data infrastructure, that provides data for health-related research, to meet tomorrow's health challenges. NHRSP aims to make health research more sustainable, efficient and responsive to health challenges, through research data sharing and re-cycling, in accordance with the ethical standards of scientific research.
Explore, search, and download data and metadata from your experiments and from public Open Data. The ESRF data repository is intended to store and archive data from photon science experiments done at the ESRF and to store digital material like documents and scientific results which need a DOI and long term preservation. Data are made public after an embargo period of maximum 3 years.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDAā€™s services include automated archiving of imaging studies from all of the Universityā€™s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
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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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The team have established the CardiacAI Data Repository that brings large amounts of Australian healthcare data together in a secure environment with strict conditions for use of these data with an appropriate level of oversight of research activities. The CardiacAI Data Repository collects de-identified EMR data about cardiovascular patients who are admitted to a group of urban and regional hospitals in NSW and links this with state-wide hospital and emergency deparment visit and mortality data and mobile-health remote monitoring data.
The Survey of Health, Ageing and Retirement in Europe (SHARE) is a multidisciplinary and cross-national panel database of micro data on health, socio-economic status and social and family networks of more than 140,000 individuals (approximately 530,000 interviews) aged 50 or over from 28 European countries and Israel.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
Country
Population Data BC (PopData) is a multi-university, data and education resource facilitating interdisciplinary research on the determinants of human health, well-being and development. Providing a range of services to researchers and data providers, PopData strives to ensure that researchers have timely access to the data and training they need to address research questions on population health. Research using these data informs policy-making and leads to healthier communities.
The National Trauma Data BankĀ® (NTDB) is the largest aggregation of trauma registry data ever assembled. The goal of the NTDB is to inform the medical community, the public, and decision makers about a wide variety of issues that characterize the current state of care for injured persons. Registry data that is collected from the NTDB is compiled annually and disseminated in the forms of hospital benchmark reports, data quality reports, and research data sets. Research data sets that can be used by researchers. To gain access to NTDB data, researchers must submit requests through our online application process