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Found 9 result(s)
OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.
<<<!!!<<< The repository is no longer available. >>>!!!>>> Selected TOXMAP data can be accesse from the following sites: U.S. EPA Toxics Release Program (TRI) (https://www.epa.gov/toxics-release-inventory-tri-program) U.S. EPA Superfund Program (https://www.epa.gov/superfund) U.S. EPA Facilities Registry System (FRS) (https://www.epa.gov/frs) U.S. EPA Clean Air Markets Program (https://www.epa.gov/airmarkets) U.S. EPA Geospatial Applications (https://www.epa.gov/geospatial/epa-geospatial-applications) U.S. NIH NCI Surveillance, Epidemiology, and End Results Program (SEER) (https://seer.cancer.gov/) Government of Canada National Pollutant Release Inventory (NPRI) (https://www.canada.ca/en/services/environment/pollution-waste-management/national-pollutant-release-inventory.html) U.S. Census Bureau (https://www.census.gov/) U.S. Nuclear Regulatory Commission (NRC) (https://www.nrc.gov/) >>>!!!>>>
>>>!!!<<< This site is going away on April 1, 2021. General access to the site has been disabled and community users will see an error upon login. >>>!!!<<< Socrata’s cloud-based solution allows government organizations to put their data online, make data-driven decisions, operate more efficiently, and share insights with citizens.
!!! <<< 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).
Queen's University Dataverse is the institutional open access research data repository for Queen's University, featuring Queen's University Biological Station (QUBS) which includes research related to ecology, evolution, resource management and conservation, GIS, climate data, and environmental science.
Satellite-tracked drifting buoys ("drifters") collect measurements of upper ocean currents and sea surface temperatures (SST) around the world as part of the Global Drifter Program. Drifter locations are estimated from 16-20 satellite fixes per day, per drifter. The Drifter Data Assembly Center (DAC) at NOAA's Atlantic Oceanographic and Meteorological Laboratory (AOML) assembles these raw data, applies quality control procedures, and interpolates them via kriging to regular six-hour intervals. The raw observations and processed data are archived at AOML and at the Marine Environmental Data Services (MEDS) in Canada. Two types of data are available: "metadata" contains deployment location and time, time of drogue (sea anchor) loss, date of final transmission, etc. for each drifter. "Interpolated data" contains the quality-controlled, interpolated drifter observations.
Including data and software from CrystalEye is this a open-access collection of crystal structures of organic, inorganic, metal-organic compounds and minerals, excluding biopolymers. At present, this is the most comprehensive open resource for small molecule structures, freely available to all scientists in Lithuania and worldwide. Including data and software from CrystalEye, developed by Nick Day at the department of Chemistry, the University of Cambridge under supervision of Peter Murray-Rust.
<<<!!!<<< 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.