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Found 4 result(s)

European Environment Agency, Datasets

EEA

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The European Environment Agency (EEA) is an agency of the European Union. Our task is to provide sound, independent information on the environment. We are a major information source for those involved in developing, adopting, implementing and evaluating environmental policy, and also the general public. Currently, the EEA has 33 member countries. EEA's mandate is: To help the Community and member countries make informed decisions about improving the environment, integrating environmental considerations into economic policies and moving towards sustainability To coordinate the European environment information and observation network (Eionet)

Potsdam Carte du Ciel Plates

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Publication of scans of photographic plates from the so-called "Potsdam zone" of the Carte du Ciel project (32 deg to 39 deg). A total of 977 plates of 2 square degree sky regions was observed and recorded between 1913 to 1924. Since Potsdam Observatory ended participation in the Carte du Ciel project, these observations were so far not analysed or published. Plates were scanned in by a flat bed scanner in 2007-2008. Limitations in astrometric precision as well are to be expected, and specific observational restrains apply, such as multiple exposures on certain plates (see literature)

Astrophysics Source Code Library

ASCL

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The Astrophysics Source Code Library (ASCL) is a free online registry for source codes of interest to astronomers and astrophysicists and lists codes that have been used in research that has appeared in, or been submitted to, peer-reviewed publications. The ASCL is citable by using the unique ascl ID assigned to each code. The ascl ID can be used to link to the code entry by prefacing the number with ascl.net (i.e., ascl.net/1201.001).

PSnpBind

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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.