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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.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
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 Neuroscience Information Framework is a dynamic index of data, materials, and tools. Please note, we do not accept direct data deposits, but if you wish to make your data repository or database available through our search, please contact us. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.
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.
<<<!!!<<< In November 2023 the Donders Repository was merged with the Radboud Data Repository: https://www.re3data.org/repository/r3d100013607. Researchers should now use the RDR at https://data.ru.nl instead of the Donders Repository (https://data.donders.ru.nl). All datasets of the Donders Repository are findable on the web portal of the RDR, and the Donders Repository URLs redirect to the RDR web portal. >>>!!!>>> The repository of the Donders Institute for Brain, Cognition and Behaviour at the Radboud University was used to manage, share and publish neuroscience and neuroimaging data, including MRI, EEG, MEG and other types of research data.
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.