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Found 385 result(s)
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
The Radio Telescope Data Center (RTDC) reduces, archives, and makes available on its web site data from SMA and the CfA Millimeter-wave Telescope. The whole-Galaxy CO survey presented in Dame et al. (2001) is a composite of 37 separate surveys. The data from most of these surveys can be accessed. Larger composites of these surveys are available separately.
Country
Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
The SURF Data Repository is a user-friendly web-based data publication platform that allows researchers to store, annotate and publish research datasets of any size to ensure long-term preservation and availability of their data. The service allows any dataset to be stored, independent of volume, number of files and structure. A published dataset is enriched with complex metadata, unique identifiers are added and the data is preserved for an agreed-upon period of time. The service is domain-agnostic and supports multiple communities with different policy and metadata requirements.
Tropicos® was originally created for internal research but has since been made available to the world’s scientific community. All of the nomenclatural, bibliographic, and specimen data accumulated in MBG’s electronic databases during the past 30 years are publicly available here.
The Drosophila Synthetic Population Resource (DSPR) consists of a new panel of over 1700 recombinant inbred lines (RILs) of Drosophila melanogaster, derived from two highly recombined synthetic populations, each created by intercrossing a different set of 8 inbred founder lines (with one founder line common to both populations). Complete genome sequence data for the founder lines are available, and in addition, there is a high resolution genetic map for each RIL. The DSPR has been developed as a community resource for high-resolution QTL mapping and is intended to be used widely by the Drosophila community.
Country
The transfer unit for data and biomaterials at the interface between Community Medicine and Molecular Medicine at the Medical Faculty of the University Medicine Greifswald enables the use of data from the studies of the research association Community Medicine (FVCM), e.g. the "Study of Health in Pomerania" (SHIP), "Study of Neonates in Pomerania" (SNiP), or "Greifswald Approach to Individualized Medicine" (GANI_MED), coordinated with regard to application, provision and documentation.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
The NCBI Short Genetic Variations database, commonly known as dbSNP, catalogs short variations in nucleotide sequences from a wide range of organisms. These variations include single nucleotide variations, short nucleotide insertions and deletions, short tandem repeats and microsatellites. Short Genetic Variations may be common, thus representing true polymorphisms, or they may be rare. Some rare human entries have additional information associated withthem, including disease associations, genotype information and allele origin, as some variations are somatic rather than germline events. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017***
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
The JPL Tropical Cyclone Information System (TCIS) was developed to support hurricane research. There are three components to TCIS; a global archive of multi-satellite hurricane observations 1999-2010 (Tropical Cyclone Data Archive), North Atlantic Hurricane Watch and ASA Convective Processes Experiment (CPEX) aircraft campaign. Together, data and visualizations from the real time system and data archive can be used to study hurricane process, validate and improve models, and assist in developing new algorithms and data assimilation techniques.
A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
Central data management of the USGS for water data that provides access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands. Includes data on water use and quality, groundwater, and surface water.
<<<!!!>>> NVO - National Virtual Observatory is closed now <<<!!! >>> The National Virtual Observatory (NVO) was the predecessor of the VAO. It was a research project aimed at developing the technologies that would be used to build an operational Virtual Observatory. With the NVO era now over, a new organization has been funded in its place, with the explicit goal of creating useful tools for users to take advantage of the groundwork laid by the NVO. To carry on with the NVO's goals, we hereby introduce you to the Virtual Astronomical Observatory http://www.usvao.org/
The POES satellite system offers the advantage of daily global coverage, by making nearly polar orbits 14 times per day approximately 520 miles above the surface of the Earth. The Earth's rotation allows the satellite to see a different view with each orbit, and each satellite provides two complete views of weather around the world each day. NOAA partners with the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) to constantly operate two polar-orbiting satellites – one POES and one European polar-orbiting satellite called Metop. NOAA's Polar Orbiting Environmental Satellites (POES) carry a suite of instruments that measure the flux of energetic ions and electrons at the altitude of the satellite. This environment varies as a result of solar and geomagnetic activity. Beginning with the NOAA-15 satellite, an upgraded version of the Space Environment Monitor (SEM-2) has been flown.
ScienceBase provides access to aggregated information derived from many data and information domains, including feeds from existing data systems, metadata catalogs, and scientists contributing new and original content. ScienceBase architecture is designed to help science teams and data practitioners centralize their data and information resources to create a foundation needed for their work. ScienceBase, both original software and engineered components, is released as an open source project to promote involvement from the larger scientific programming community both inside and outside the USGS.
>>>!!!<<< 2019-12-03: The repository is no longer available >>>!!!<<< Please use https://www.cfa.harvard.edu/amp/ampdata/kurucz23/sekur.html The atomic line data used in this database are taken from Bob Kurucz' CD-ROM 23 of spectroscopic line calculations. The database contains all lines of the file "gfall.dat" with the following items for each line: Wavelength; loggf; element code; lower level: energy, J, configuration; upper level: energy, J, configuration; gamma r; gamma s; gamma w; reference code. CD-ROM 23 has all the atomic line data with good wavelengths in one large file and in one file for each species. The big file is also divided into 10 nm and 100 nm sections for convenience. Also given are hyperfine line lists for neutral Sc, V, Mn, and Co that were produced by splitting all the energy levels for which laboratory data are available (only a small fraction).
>>>!!!Bacterial (BCSDB) and Plant&Fungal (PFCSDB) carbohydrate structure databases have been merged into a single database, CSDB!!!<<< BCSDB database is aimed at provision of structural, bibliographic, taxonomic and related information on bacterial carbohydrate structures. Two key points of this service are: covering - is above 90% in the scope of bacterial carbohydrates. This means the negative search answer remains valuable scientific information. And consistence - we manually check the data, and aim at hight quality error-free content. The main source of data is a retrospective literature analysis. About 25% of data were imported from CCSD (Carbbank, ceased in 1997, University of Georgia, Athens; structures published before 1995) with subsequent manual curation and approval. Current coverage is displayed in red on the top of the left menu. The time lag between publication of new data and their deposition ~ 1 year. The scope is "bacterial carbohydrates" and covers nearly all structures of this class published up to 2016. Bacterial means that a structure has been found in bacteria or obtained by modification of those found in bacteria. Carohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds, in which at least one residue is a sugar or its derivative.
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>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
!!! <<< the repository is offline, please use: https://www.re3data.org/repository/r3d100011650 >>> !!! The USGODAE Project consists of United States academic, government and military researchers working to improve assimilative ocean modeling as part of the International GODAE Project. GODAE hopes to develop a global system of observations, communications, modeling and assimilation, that will deliver regular, comprehensive information on the state of the oceans, in a way that will promote and engender wide utility and availability of this resource for maximum benefit to the community. The USGODAE Argo GDAC is currently operational, serving daily data from the following national DACs: Australia (CSIRO), Canada (MEDS), China (2: CSIO and NMDIS), France (Coriolis), India (INCOIS), Japan (JMA), Korea (2: KMA and Kordi), UK (BODC), and US (AOML).
The International Ocean Discovery Program’s (IODP) Gulf Coast Repository (GCR) is located in the Research Park on the Texas A&M University campus in College Station, Texas. This repository stores DSDP, ODP, and IODP cores from the Pacific Ocean, the Caribbean Sea and Gulf of Mexico, and the Southern Ocean. A satellite repository at Rutgers University houses New Jersey/Delaware land cores 150X and 174AX.
IDEALS is an institutional repository that collects, disseminates, and provides persistent and reliable access to the research and scholarship of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students, and in some cases undergraduate students, can deposit their research and scholarship directly into IDEALS. Departments can use IDEALS to distribute their working papers, technical reports, or other research material. Contact us at https://www.ideals.illinois.edu/feedback for more information.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.