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Found 68 result(s)
The Whitehall II study was established to explore the relationship between socio-economic status, stress and cardiovascular disease. A cohort of 10,308 participants aged 35-55, of whom 3,413 were women and 6,895 men, was recruited from the British Civil Service in 1985. Since this first wave of data collection, self-completion questionnaires and clinical data have been collected from the cohort every two to five years with a high level of participation. Data collection is intended to continue until 2030.
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Since 2004, the Leibniz Institute for Prevention Research and Epidemiology – BIPS has been working on the establishment and maintenance of the project-based German Pharmacoepidemiological Research Database (short GePaRD). GePaRD is based on claims data from statutory health insurance (SHI) providers and currently includes information on about 20 million persons who have been insured with one of the participating providers since 2004. Per data year, there is information on approximately 17% of the general population from all geographical regions of Germany.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).
The Malaria Atlas Project (MAP) brings together researchers based around the world with expertise in a wide range of disciplines from public health to mathematics, geography and epidemiology. We work together to generate new and innovative methods of mapping malaria risk. Ultimately our goal is to produce a comprehensive range of maps and estimates that will support effective planning of malaria control at national and international scales.
The Netherlands Cancer Registry is the national registration since 1989, providing statistics on cancer in the Netherlands. The registry is maintained by the Netherlands Comprehensive Cancer Organisation (IKNL). Data on incidence, prevalence, survival, mortality can be viewed in NCR data & figures on the IKNL website.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
Country
The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
Country
With ARS - Antimicrobial Resistance Surveillance in Germany - the infrastructure for a nationwide surveillance of antimicrobial resistance has been established, which covers both the inpatient medical care and the ambulatory care sector. This is intended to reliable data on the epidemiology of antimicrobial resistance in Germany and differential statements provided by structural features of the health care and by region are possible. ARS is designed as a laboratory-based surveillance system for continuous collection of resistance data from routine for the full range of clinically relevant bacterial pathogens. Project participants and thus data suppliers are laboratories that analyze samples of medical facilities and doctors' offices microbiologically.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
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ZB MED's Repository for Life Sciences offers authors the chance to publish their scientific texts and research data from the fields of medicine, health, nutritional, environmental and agricultural sciences. In accordance with the principles of Open Access, these publications can be accessed over the Internet without restrictions. There is no charge to publish, archive or use the documents.
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DDBJ Sequence Read Archive (DRA) is the public archive of high throughput sequencing data. DRA stores raw sequencing data and alignment information to enhance reproducibility and facilitate new discoveries through data analysis. DRA is a member of the International Nucleotide Sequence Database Collaboration (INSDC) and archiving the data in a close collaboration with NCBI Sequence Read Archive (SRA) and EBI Sequence Read Archive (ERA).
The Progenetix database provides an overview of copy number abnormalities in human cancer from currently 32548 array and chromosomal Comparative Genomic Hybridization (CGH) experiments, as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. The cancer profile data in Progenetix was curated from 1031 articles and represents 366 different cancer types, according to the International classification of Diseases in Oncology (ICD-O).
COViMS (COVID-19 Infections in MS & Related Diseases) is a joint effort of the National MS Society, Consortium of MS Centers and Multiple Sclerosis Society of Canada to capture information on outcomes of people with MS and other CNS demyelinating diseases (Neuromyelitis Optica, or MOG antibody disease) who have developed COVID-19.
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The German National Cohort (NAKO) has been inviting men and women aged between 20 and 69 to 18 study centers throughout Germany since 2014. The participants are medically examined and questioned about their living conditions. The GNC’s aim is to investigate the causes of chronic diseases, such as cancer, diabetes, cardiovascular diseases, rheumatism, infectious diseases, and dementia in order to improve prevention, early diagnoses and treatment of these very widely spread diseases.
The European Mouse Mutant Archive – EMMA is a non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant mouse strains essential for basic biomedical research. The laboratory mouse is the most important mammalian model for studying genetic and multi-factorial diseases in man. The comprehensive physical and data resources of EMMA support basic biomedical and preclinical research, and the available research tools and mouse models of human disease offer the opportunity to develop a better understanding of molecular disease mechanisms and may provide the foundation for the development of diagnostic, prognostic and therapeutic strategies.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.