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Found 2 result(s)

Cellosaurus

Cellosaurus - a knowledge resource on cell lines

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The Cellosaurus is a knowledge resource on cell lines. It attempts to describe all cell lines used in biomedical research. Its scope includes: Immortalized cell lines, Naturally immortal cell lines (example: stem cell lines), Finite life cell lines when those are distributed and used widely, Vertebrate cell line with an emphasis on human, mouse and rat cell lines, Invertebrate (insects and ticks) cell lines. Its scope does not include: Primary cell lines (with the exception of the finite life cell lines described above), Plant cell lines. Cellosaurus was initiated to be used as a cell line controlled vocabulary in the context of the neXtProt knowledgebase, but it quickly become apparent that there was a need for a cell line knowledge resource that would serve the needs of individual researchers, cell line distributors and bioinformatic resources. This leads to an increase of the scope and depth of the content of the Cellosaurus. The Cellosaurus is a participant of the Resource Identification Initiative and contributes actively to the work of the International Cell Line Authentication Committee (ICLAC). It is a Global Core Biodata Resource, an ELIXIR Core Data Resource and an IRDiRC Recognized Resource.

UCSD Metabolomics Workbench

Metabolomics Workbench

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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.