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Found 14 result(s)
Content type(s)
NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.
Country
Base of Knowledge Wrocław University of Environmental and Life Sciences / Research Data Repository is an institutional open research data repository, offering the possibility to deposit datasets (as well as publications) created by researchers, PhD candidates and students of Wrocław University of Environmental and Life Sciences. It is intended for scientific data from the disciplines related to the University’s profile. It is a platform where research data can be safely collected, stored and openly shared with others, obtaining a permanent Digital Object Identifier (DOI) for each dataset and choosing a data usage license. Research Data Repository applies the FAIR Principles (data is findable, accessible, interoperable and reusable).
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
Country
DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
Content type(s)
Country
Rīga Stradiņš University (RSU) Dataverse is created for RSU researchers to deposit their data there after the end of research projects or other research activities, especially in cases when there are no trusted field specific repositories.
Country
MDM-Portal (Medical Data Models) is a meta-data registry for creating, analyzing, sharing and reusing medical forms. It serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It contains forms in the system-independent CDISC Operational Data Model (ODM) format with more than 500,000 data-elements. The Portal provides numerous core data sets, common data elements or data standards, code lists and value sets. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc.
RIVMdata is a metadata catalog. This catalog is filled with the metadata of RIVM datasets. ISO 19115 and DCAT standards are used as the metadata standards. The catalog consists of an internal site, which is only accessible to RIVM employees, and an external site, in which the metadata is accessible to the general public.
Content type(s)
The MDR harvests metadata on data objects from a variety of sources within clinical research (e.g. trial registries, data repositories) and brings that together in a single searchable portal. The metadata is concerned with discoverability, access and provenance of the data objects (which because the data may be sensitive will often be available under a controlled access regime). At the moment (01/2021) the MDR obtains study data from: Clinical Trials.gov (CTG), The European Clinical Trials Registry (EUCTR), ISRCTN, The WHO ICTRP
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
Country
The Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.