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<<<!!!<<< Phasing out support for the Database of Genomic Variants archive (DGVa). The submission, archiving, and presentation of structural variation services offered by the DGVa is transitioning to the European Variation Archive (EVA) https://www.re3data.org/repository/r3d100011553. All of the data shown in the DGVa website is already searchable and browsable from the EVA Study Browser. Submission of structural variation data to EVA is done using the VCF format. The VCF specification allows representing multiple types of structural variants such as insertions, deletions, duplications and copy-number variants. Other features such as symbolic alleles, breakends, confidence intervals etc., support more complex events, such as translocations at an imprecise position. >>>!!!>>>
This site provides access to complete, annotated genomes from bacteria and archaea (present in the European Nucleotide Archive) through the Ensembl graphical user interface (genome browser). Ensembl Bacteria contains genomes from annotated INSDC records that are loaded into Ensembl multi-species databases, using the INSDC annotation import pipeline.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.