Filter
Reset all

Subjects

Content Types

Countries

AID systems

Data access

Data access restrictions

Database access

Data licenses

Data upload

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

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
  • 1 (current)
Found 3 result(s)
Country
The purpose of the Biobank is to accelerate future research projects and build health monitoring opportunities on a nationally-representative sample of Canadians. The Biobank receives samples from surveys like CHMS or CCAHS that collect dried blood spot, blood, urine, and saliva samples from consenting participants. These samples are stored in a secure location for future health studies. To obtain approval for the use of these samples, research projects undergo a thorough scientific, ethical, and security review process.
Country
CanPath is Canada’s largest population health cohort and a national platform for population-level health research.It is a unique Canadian platform allowing scientists to explore the complex factors that contribute to disease. It is a deeply characterized cohort of individuals who have provided broad consent and now include two per cent of all Canadians between 30 and 74 years of age. CanPath can save researchers time — sometimes up to a decade — associated with arranging and measuring their own population samples. Researchers around the world can readily integrate CanPath data into their own studies. The standardization and harmonization of data across CanPath’s regional cohorts has been facilitated by Maelstrom Research.
<<<!!!<<< 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.