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The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.
The University has followed all of the children born in Aberdeen in 1921, 1936, and 1950-1956 as they grow and age. Collectively these groups are known as the ABERDEEN BIRTH COHORTS, and are a jewel in the crown of Scottish health research and have helped to advance our understanding of aging well. The Children of the 1950s study is a population-based resource for the study of biological and social influences on health across the life-course and between generations.
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The Maelstrom Catalogue provides a user-friendly solution for data discovery. It contains comprehensive information about epidemiological research networks and studies, and the data they have collected. It also provides information about harmonized data generated by these research networks.
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 National Sleep Research Resource (NSRR) is an NHLBI-supported repository for sharing large amounts of sleep data (polysomnography, actigraphy and questionnaire-based) from multiple cohorts, clinical trials, and other data sources. Launched in April 2014, the mission of the NSRR is to advance sleep and circadian science by supporting secondary data analysis, algorithmic development, and signal processing through the sharing of high-quality data sets.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials