Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Certificates

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
Found 184 result(s)
PharmGKB is a comprehensive resource that curates knowledge about the impact of genetic variation on drug response for clinicians and researchers. PharmGKB brings together the relevant data in a single place and adds value by combining disparate data on the same relationship, making it easier to search and easier to view the key aspects and by interpreting the data.PharmGKB provide clinical interpretations of this data, curated pathways and VIP summaries which are not found elsewhere.
TRAILS is a prospective cohort study, which started in 2001 with population cohort and 2004 with a clinical cohort (CC). Since then, a group of 2500 young people from the Northern part of the Netherlands has been closely monitored in order to chart and explain their mental, physical, and social development. These TRAILS participants have been measured every two to three years, by means of questionnaires, interviews, and all kinds of tests. By now, we have collected information that spans the total period from preadolescence up until young adulthood. One of the main goals of TRAILS is to contribute to the knowledge of the development of emotional and behavioral problems and the (social) functioning of preadolescents into adulthood, their determinants, and underlying mechanisms.
Country
SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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 Fragile Families and Child Wellbeing Study changed its name to The Future of Families and Child Wellbeing Study (FFCWS). Note that all documentation issued prior to January 2023 contains the study’s former name. Any further reference to FFCWS should kindly observe this name change. The Fragile Families & Child Wellbeing Study is following a cohort of nearly 5,000 children born in large U.S. cities between 1998 and 2000 (roughly three-quarters of whom were born to unmarried parents). We refer to unmarried parents and their children as “fragile families” to underscore that they are families and that they are at greater risk of breaking up and living in poverty than more traditional families. The core Study was originally designed to primarily address four questions of great interest to researchers and policy makers: (1) What are the conditions and capabilities of unmarried parents, especially fathers?; (2) What is the nature of the relationships between unmarried parents?; (3) How do children born into these families fare?; and (4) How do policies and environmental conditions affect families and children?
The Infectious Diseases Data Observatory (IDDO) assembles clinical, laboratory and epidemiological data on a collaborative platform to be shared with the research and humanitarian communities. The data are analysed to generate reliable evidence and innovative resources that enable research-driven responses to the major challenges of emerging and neglected infections. Access is available to individual patient data held for malaria and Ebola virus disease. Resources for visceral leishmaniasis, schistosomiasis and soil transmitted helminths, Chagas disease and COVID-19 are under development. IDDO contains the following repositories : COVID-19 Data Platform, Chagas Data Platform, Schistosomiasis & Soil Transmitted Helminths Data Platform, Visceral Leishmaniasis Data Platform, Ebola Data Platform, WorldWide Antimalarial Resistance Network (WWARN)
Country
Contains data on patients who have been tested for COVID-19 (whether positive or negative) in participating health institutions in Brazil. This initiative makes available three kinds of pseudonymized data: demographics (gender, year of birth, and region of residency), clinical and laboratory exams. Additional hospitalization information - such as data on transfers and outcomes - is provided when available. Clinical, lab, and hospitalization information is not limited to COVID-19 data, but covers all health events for these individuals, starting November 1st 2019, to allow for comorbidity studies. Data are deposited periodically, so that health information for a given individual is continuously updated to time of new version upload.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
The Africa Health Research Institute (AHRI) has published its updated analytical datasets for 2016. The datasets cover socio-economic, education and employment information for individuals and households in AHRI’s population research area in rural northern KwaZulu-Natal. The datasets also include details on the migration patterns of the individuals and households who migrated into and out of the surveillance area as well as data on probable causes of death for individuals who passed away. Data collection for the 2016 individual interviews – which involves a dried blood spot sample being taken – is still in progress, and therefore datasets on HIV status and General Health only go up to 2015 for now. Over the past 16 years researchers have developed an extensive longitudinal database of demographic, social, economic, clinical and laboratory information about people over the age of 15 living in the AHRI population research area. During this time researchers have followed more than 160 000 people, of which 92 000 are still in the programme.
CalSurv is a comprehensive information on West Nile virus, plague, malaria, Lyme disease, trench fever and other vectorborne diseases in California — where they are, where they’ve been, where they may be headed and what new diseases may be emerging.The CalSurv Web site serves as a portal or a single interface to all surveillance-related Web sites in California.
CDC.gov is the Centers for Disease Control and Prevention primary online communication channel. CDC.gov provides users with credible, reliable health information on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety,Life Stages and Populations, Travelers' Health, Workplace Safety and Health
>>> !!! the repository is offline !!! <<< More information see: https://dknet.org/about/NURSA_Archive All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer. To access these datasets, dkNET provides users with the information of 527 transcriptomic datasets that contain data related to nuclear receptors and nuclear receptor coregulators in the NURSA Datasets table view and redirects users to the current SPP dataset page. Once users find the specific dataset of research interest, users can download the dataset by clicking DOI and then clicking the Download Dataset button at the Signaling Pathways Project webpage. See https://www.re3data.org/repository/r3d100013650
The Twenty-07 Study was set up in 1986 in order to investigate the reasons for differences in health by socio-economic circumstances, gender, area of residence, age, ethnic group, and family type. 4510 people are being followed for 20 years. The initial wave of data collection took place in 1987/8, when respondents were aged 15, 35 and 55. The final wave of data collection took place in 2007/08 when respondents were aged 35, 55 and 75. In this way the Twenty-07 Study provides us with unique opportunities to investigate both the changes in people's lives over 20 years and how they affect their health, and the differences in people's experiences at the same ages 20 years apart, and how these have different effects on their health.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
Country
The Biobanque québécoise de la COVID-19 (BQC19) is a pan-provincial initiative that collects, stores and shares data and blood samples from COVID-19 patients, both severe and non-severe cases and control cases, in an effort to respond effectively to the public health challenges posed by the pandemic. BQC19 believes that better understanding the disease will help society in returning to social activities and in preparing for future pandemics. It sees access to high-quality samples and data as essential in fulfilling research and works to bring about national and international research collaborations.
Country
MDM-Portal (Medical Data Models) is a meta-data registry for creating, analyzing, sharing and reusing medical forms. It serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It contains forms in the system-independent CDISC Operational Data Model (ODM) format with more than 500,000 data-elements. The Portal provides numerous core data sets, common data elements or data standards, code lists and value sets. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc.
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).
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.