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The International Service of Geomagnetic Indices (ISGI) is in charge of the elaboration and dissemination of geomagnetic indices, and of tables of remarkable magnetic events, based on the report of magnetic observatories distributed all over the planet, with the help of ISGI Collaborating Institutes. The interaction between the solar wind, including plasma and interplanetary magnetic field, and the Earth's magnetosphere results in a transfer of energy and particles inside the magnetosphere. Solar wind characteristics are highly variable, and they have actually a direct influence on the shape and size of the magnetosphere, on the amount of transferred energy, and on the way this energy is dissipated. It is clear that the great diversity of sources of magnetic variations give rise to a great complexity in ground magnetic signatures. Geomagnetic indices aim at describing the geomagnetic activity or some of its components. Each geomagnetic index is related to different phenomena occurring in the magnetosphere, ionosphere and deep in the Earth in its own unique way. The location of a measurement, the timing of the measurement and the way the index is calculated all affect the type of phenomenon the index relates to. The IAGA endorsed geomagnetic indices and lists of remarkable geomagnetic events constitute unique temporal and spatial coverage data series homogeneous since middle of 19th century.
STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations; they are derived from four sources: - Genomic Context - High-throughput Experiments - (Conserved) Coexpression - Previous Knowledge STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable.
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.