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Found 6 result(s)

DataverseNO

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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.

MyTardis

Tardis

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MyTardis began at Monash University to solve the problem of users needing to store large datasets and share them with collaborators online. Its particular focus is on integration with scientific instruments, instrument facilities and research lab file storage. Our belief is that the less effort a researcher has to expend safely storing data, the more likely they are to do so. This approach has flourished with MyTardis capturing data from areas such as protein crystallography, electron microscopy, medical imaging and proteomics and with deployments at Australian institutions such as University of Queensland, RMIT, University of Sydney and the Australian Synchrotron. Data access via https://www.massive.org.au/ and https://store.erc.monash.edu.au/experiment/view/104/ and see 'remarks'.

doRiNA

database of RNA interactions in post-transcriptional regulation

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doRiNA is a database of transcriptome-wide binding site data for RNA binding proteins and microRNAs

UCL Research Data Repository

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The UCL Research Data Repository is the institutional data repository of University College London. Based on Figshare, it accepts data deposits from UCL staff and doctoral students from all disciplines. Depositors are encouraged to use CC0 licences to make their data available to the widest possible range of users and the widest range of uses.

Population Health Data Archive

PHDA

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The National Population Health Data Center (NPHDC) is one of the 20 national science data center approved by the Ministry of Science and Technology and the Ministry of Finance. The Population Health Data Archive (PHDA) is developed by NPHDC relying on the Institute of Medical Information, Chinese Academy of Medical Sciences. PHDA mainly receives scientific data from science and technology projects supported by the national budget, and also collects data from other multiple sources such as medical and health institutions, research institutions and social individuals, which is oriented to the national big data strategy and the healthy China strategy. The data resources cover basic medicine, clinical medicine, public health, traditional Chinese medicine and pharmacy, pharmacy, population and reproduction. PHDA supports data collection, archiving, processing, storage, curation, verification, certification and release in the field of population health. Provide multiple types of data sharing and application services for different hierarchy users and help them find, access, interoperate and reuse the data in a safe and controlled environment. PHDA provides important support for promoting the open sharing of scientific data of population health and domestic and foreign cooperation.

ALSoD

ALS Online Database

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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.