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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.
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).
Synapse is an open source software platform that clinical and biological data scientists can use to carry out, track, and communicate their research in real time. Synapse enables co-location of scientific content (data, code, results) and narrative descriptions of that work.
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.