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Found 14 result(s)
The Cognitive Function and Ageing Studies (CFAS) are population based studies of individuals aged 65 years and over living in the community, including institutions, which is the only large multi-centred population-based study in the UK that has reached sufficient maturity. There are three main studies within the CFAS group. MRC CFAS, the original study began in 1989, with three of its sites providing a parent subset for the comparison two decades later with CFAS II (2008 onwards). Subsequently another CFAS study, CFAS Wales began in 2011.
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.
***<<<!!!>>> *** Stated 2017-08-28: To accommodate a wider scope of ophthalmic data, we launched our new Rotterdam Ophthalmic Data Repository. Please visit http://www.rodrep.com/ for all data sets. *** The ORGIDS site will no longer be updated! ***<<<!!!>>>***Through this portal, we will make data sets available that result from our glaucoma research. This includes visual fields, various imaging modalities and other data from both glaucomatous and normal subjects.The data was acquired during more than a decade.
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 PRO-ACT platform houses the largest ALS clinical trials dataset ever created. It is a powerful tool for biomedical researchers, statisticians, clinicians, or anyone else interested in "Big Data." PRO-ACT merges data from existing public and private clinical trials, generating an invaluable resource for the design of future ALS clinical trials. The database will also contribute to the identification of unique observations, novel correlations, and patterns of ALS disease progression, as well as a variety of still unconsidered analyses. More than 600,000 people around them world are battling ALS. The disease strikes indiscriminately, and typically patients will die within 2-5 years following diagnosis. Currently, there are no effective treatments or a cure for ALS. Users of PRO-ACT are helping to accelerate the discovery, development, and delivery of ALS treatments, which will provide hope to patients and their families.
The Substance Abuse and Mental Health Data Archive (SAMHDA) is an initiative funded under contract HHSS283201500001C with the Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services (HHS). CBHSQ has primary responsibility for the collection, analysis, and dissemination of SAMHSA's behavioral health data. Public use files and restricted use files are provided. CBHSQ promotes the access and use of the nation's substance abuse and mental health data through SAMHDA. SAMHDA provides public-use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health.
The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. The NDA provides infrastructure for sharing research data, tools, methods, and analyses enabling collaborative science and discovery. De-identified human subjects data, harmonized to a common standard, are available to qualified researchers. Summary data is available to all. The primary point of entry to the NDA is currently through the National Database for Autism Research (NDAR) website, which serves the autism research community. All NDA repositories can be accessed through this website for data contribution and querying with other scientific communities, allowing for aggregation and secondary analysis of data.
The DPUK Data Portal brings together records of over 2 million people in a free-to-access resource. Researchers can identify which cohorts are relevant to them, apply for access to the data and then analyse it in a secure, remote environment with a complete data linkage and analysis package.
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>>>!!!<<< eyemoviepedia.com was shut down in the course of 2021 https://www.zbmed.de/en/research/completed-projects/eyemoviepedia/ >>>!!!<<< The eyeMoviePedia videos moved successively to be found on PUBLISSO-Repository for Life Sciences (FRL) in the future. https://www.re3data.org/repository/r3d100013523 To view the new eyeMoviePedia collection see: https://repository.publisso.de/resource?query[0][term]=%22https%3A%2F%2Fd-nb.info%2Fgnd%2F1223212661%22
The eyeGENE® Research Resource is open for approved research studies. Application details here Researchers and clinicians are actively developing gene-based therapies to treat ophthalmic genetic diseases that were once considered untreatable.
ALSoD is a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.