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Found 14 result(s)
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.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
Sandrart.net: A net-based research platform on the history of art and culture in the 17th century. The project’s main goal was an annotated, enriched and web-based edition of Joachim von Sandrart’s Teutscher Academie der Edlen Bau, Bild- und Mahlerey-Künste (1675–80), one of the most important source texts of the early modern period. Having lived and worked in a number of places throughout Europe, Sandrart’s biographical background makes his writings (with first-hand narrations on art, artists and art collections) a work of European dimension.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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MaxQB stores and displays collections of large proteomics projects and allows joint analysis and comparison. As a first dataset is contains proteome data of 11 different human cell lines. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted.
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Plastics are widely used in our economy and each year, at least 350-400 million tons are being produced at a global level. Due to poor recycling and low circular use, tens of millions of tons accumulate annually in marine and terrestrial environments. While it has become obvious that micro and macroplastics contaminate our environments recent research has identified few bacteria and fungi actively degrading plastics by enzymatic reactions. In general these are promiscuous enzymes (hydrolases) acting on low crystaline and mostly low density polymers of PET, ester-based PUR and oligomers of PA. Notably today, no enzymes have been characterized on a biochemical level for polymeric and crystaline PE, ether-based PUR, PS, PVC, PP. While many publications report on plastic degradation often, no convincing biochemical data have been published. Therefore the PAZy database lists exclusively biochemically characterized plastic-active enzymes. Predicted and putative enzymes that were not characterized on a biochemical, functional or structural level are not included in the PAZy database. The entries are manually curated.
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LIAS is a global information system for Lichenized and Non-Lichenized Ascomycetes. It includes several interoperable data repositories. In recent years, the two core components ‘LIAS names’ and ‘LIAS light’ have been much enlarged. LIAS light is storing phenotypic trait data. They includes > 10,700 descriptions (about 2/3 of all known lichen species), each with up to 75 descriptors comprising 2,000 traits (descriptor states and values), including 800 secondary metabolites. 500 traits may have biological functions and more than 1,000 may have phylogenetic relevance. LIAS is thus one of the most comprehensive trait databases in organismal biology. The online interactive identification key for more than 10,700 lichens is powered by the Java applet NaviKey and has been translated into 19 languages (besides English) in cooperation with lichenologists worldwide. The component ‘LIAS names’ is a platform for managing taxonomic names and classifications with currently >50,000 names, including the c. 12,000 accepted species and recognized synonyms. The LIAS portal contents, interfaces, and databases run on servers of the IT Center of the Bavarian Natural History Collections and are maintained there. 'LIAS names' and ‘LIAS light’ also deliver content data to the Catalogue of Life, acting as the Global Species Database (GSD) for lichens. LIAS gtm is a database for visualising the geographic distribution of lichen traits. LIAS is powered by the Diversity Workbench database framework with several interfaces for data management and publication. The LIAS long-term project was initiated in the early 1990s and has since been continued with funding from the DFG, the BMBF, and the EU.
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This data archive of experiments studying the dynamics of pedestrians is build up by the Institute for Advanced Simulation 7: Civil Safety Research of Forschungszentrum Jülich. The landing page provides our own data of experiments. Data of research colleagues are listed within the data archive at https://ped.fz-juelich.de/extda For most of the experiments, the video recordings, as well as the resulting trajectories of single pedestrians, are available. The experiments were performed under laboratory conditions to focus on the influence of a single variable. You are very welcome to use our data for further research, as long as you name the source of the data. If you have further questions feel free to contact Maik Boltes.
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Methods of digital architectural documentation/polychromy (pilot project). Three architectural fragments were recorded with photography, architectural drawings by hand, different techniques of 3D scanning, and Reflectance Transformation Imaging (RTI).
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As a center for scientific research and evidence-based policy advice, RWI requires an effective econometric infrastructure. The increased use of individual and firm data also requires effective regulations and tools for data protection. The research division’s objectives are to advise RWI researchers in methodical questions, to develop new econometric approaches to solve concrete research questions, and to ensure data protection.
The THEMIS mission is a five-satellite Explorer mission whose primary objective is to understand the onset and macroscale evolution of magnetospheric substorms. The five small satellites were launched together on a Delta II rocket and they carry identical sets of instruments including an electric field instrument (EFI), a flux gate magnetometer (FGM), a search coil magnetometer (SCM), a electro-static analyzer, and solid state telescopes (SST). The mission consists of several phases. In the first phase, the spacecraft will all orbit as a tight cluster in the same orbital plane with apogee at 15.4 Earth radii (RE). In the second phase, also called the Dawn Phase, the satellites will be placed in their orbits and during this time their apogees will be on the dawn side of the magnetosphere. During the third phase (also known as the Tail Science Phase) the apogees will be in the magnetotail. The fourth phase is called the Dusk Phase or Radiation Belt Science Phase, with all apogees on the dusk side. In the fifth and final phase, the apogees will shift to the sunward side (Dayside Science Phase). The satellite data will be combined with observations of the aurora from a network of 20 ground observatories across the North American continent. The THEMIS-B (THEMIS-P1) and THEMIS-C (THEMIS-P2) were repurposed to study the lunar environment in 2009. The spacecraft were renamed ARTEMIS (Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon’s Interaction with the Sun), with the P1 and P2 designations maintained.
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<<<!!!<<< This repository is no longer available. PLEASE NOTE: Unfortunately, the Hustedt collection cannot be used at the moment. Since the collection was previously located in our section, this page can still be found here. We hope to be able to provide information on the further use of the collection shortly. https://www.awi.de/en/science/biosciences/polar-biological-oceanography/main-research-focus/hustedt-diatom-study-centre.html >>>!!!>>>