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The Norwegian Marine Data Centre (NMD) at the Institute of Marine Research was established as a national data centre dedicated to the professional processing and long-term storage of marine environmental and fisheries data and production of data products. The Institute of Marine Research continuously collects large amounts of data from all Norwegian seas. Data are collected using vessels, observation buoys, manual measurements, gliders – amongst others. NMD maintains the largest collection of marine environmental and fisheries data in Norway.
RADAR service offers the ability to search for research data descriptions of the Natural Resources Institute Finland (Luke). The service includes descriptions of research data for agriculture, forestry and food sectors, game management, fisheries and environment. The public web service aims to facilitate discovering subjects of natural resources studies. In addition to Luke's research data descriptions one can search metadata of the Finnish Environment Institute (SYKE). The interface between Luke and SYKE metadata services combines Luke's research data descriptions and SYKE's descriptions of spatial datasets and data systems into a unified search service.
The Arabidopsis Information Resource (TAIR) maintains a database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana . Data available from TAIR includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from our data pages to other Arabidopsis resources.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.