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Found 3 result(s)

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.

DRYAD

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Dryad is an open data publishing platform and a community committed to the open availability and routine re-use of all research data. We publish data in any format and any discipline. All Dryad data undergoes a curation process and is published under a CC0 waiver to promote reuse.

ChEMBL

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ChEMBL is a database of bioactive drug-like small molecules, it contains 2-D structures, calculated properties (e.g. logP, Molecular Weight, Lipinski Parameters, etc.) and abstracted bioactivities (e.g. binding constants, pharmacology and ADMET data). The data is abstracted and curated from the primary scientific literature, and cover a significant fraction of the SAR and discovery of modern drugs We attempt to normalise the bioactivities into a uniform set of end-points and units where possible, and also to tag the links between a molecular target and a published assay with a set of varying confidence levels. Additional data on clinical progress of compounds is being integrated into ChEMBL at the current time.