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Found 11 result(s)
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The Human Genetic Variation Database (HGVD) aims to provide a central resource to archive and display Japanese genetic variation and association between the variation and transcription level of genes. The database currently contains genetic variations determined by exome sequencing of 1,208 individuals and genotyping data of common variations obtained from a cohort of 3,248 individuals.
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
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.
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.
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The Research Data Centre (FDZ-RV) was set-up in 2004 as an integral part of the German Federal Pension Insurance (Deutsche Rentenversicherung). Since then, the Research Data Centre produced several cross-sectional and longitudinal datasets, also called Scientific Use Files (SUF), available to researchers interested in issues of retirement, disability and rehabilitation. The datasets are released on an annual basis. The Scientific Use Files are subsamples drawn from the pool of individuals who are insured in the Federal Pension Insurance. The information provided in the original datasets is necessary to administer the beneficiaries of the pension insurance.
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DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
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.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies