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Found 46 result(s)
As a department of the United States Department of Agriculture (USDA) the National Agricultural Statistics Service (NASS) continually surveys and reports on U.S. agriculture. NASS reports include production and supplies of food and fiber, prices paid and received by farmers, farm labor and wages, farm finances, chemical use, and changes in the demographics of U.S. producers. NASS provides objective and unbiased statistics of states and counties, while safeguarding the privacy of farmers and ranchers.
The USDA Economics, Statistics and Market Information System contains reports and datasets of multiple agencies within the United States Department of Agriculture, including the Agricultural Marketing Service, the Economic Research Service, the Foreign Agricultural Service, the National Agricultural Statistics Service, and the World Agricultural Outlook Board. Historical and current reports and datasets are included.
The Structure database provides three-dimensional structures of macromolecules for a variety of research purposes and allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships.
The Entrez Protein Clusters database contains annotation information, publications, structures and analysis tools for related protein sequences encoded by complete genomes. The data available in the Protein Clusters Database is generated from prokaryotic genomic studies and is intended to assist researchers studying micro-organism evolution as well as other biological sciences. Available genomes include plants and viruses as well as organelles and microbial genomes.
<<<!!!<<< NCBI announced plans to retire the Clone DB web interface. Pursuant to this retirement, starting on May 27, 2019, all web pages associated with Clone DB and CloneFinder will redirect to this blog post https://ncbiinsights.ncbi.nlm.nih.gov/?s=clone+db. Links to Clone DB from the NCBI home page will also be going away. >>>!!!>>>
<<<!!!<<< 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/) >>>!!!>>>
Born of the desire to systematize analyses from The Cancer Genome Atlas pilot and scale their execution to the dozens of remaining diseases to be studied, GDAC Firehose now sits atop terabytes of analysis-ready TCGA data and reliably executes thousands of pipelines per month. More information: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/
<<<!!!<<<The repository is no longer available <<<!!!<<< TOXNET has moved. Most content will continue to be collected and reviewed; selected information is accessible through PubChem, PubMed, and Bookshelf. If you have questions, please contact NLM Customer Support at https://support.nlm.nih.gov/ >>>!!!>>>
The U.S. Department of Energy (DOE) Joint Genome Institute (JGI) is a DOE Office of Science User Facility located at Lawrence Berkeley National Laboratory (Berkeley Lab). All data generated by the DOE Joint Genome Institute is available through this repository once the data are published or public.
The Census of Agriculture provides extensive data about U.S. agriculture at the country, state and county level. The census is conducted every 5 years, and it gathers uniform, detailed data about U.S. farms and ranches and their operators. Data from recent censuses are available in different formats, but historical censuses (back to 1840) are available in pdf format.
<<<!!!<<< As of June 30, 2017, HardinMD has been retired, although it is still findable through the WayBack Machine >>>!!!>>>
mentha archives evidence collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. The aggregated data forms an interactome which includes many organisms. mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. mentha offers eight interactomes (Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli K12, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae) plus a global network that comprises every organism, including those not mentioned. The website and the graphical application are designed to make the data stored in mentha accessible and analysable to all users. Source databases are: MINT, IntAct, DIP, MatrixDB and BioGRID.
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The National Archives and Records Administration (NARA) is the nation's record keeper. Of all documents and materials created in the course of business conducted by the United States Federal government, only 1%-3% are so important for legal or historical reasons that they are kept by us forever. Those valuable records are preserved and are available to you, whether you want to see if they contain clues about your family’s history, need to prove a veteran’s military service, or are researching an historical topic that interests you.
This site is dedicated to making high value health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of better health outcomes for all. In a recent article, Todd Park, United States Chief Technology Officer, captured the essence of what the Health Data Initiative is all about and why our efforts here are so important.
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.
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.
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<<<!!!<<< The repository is no longer available. <<<!!!<<< TOXNET's TRI is retired. Visit TRI at EPA: https://www.epa.gov/toxics-release-inventory-tri-program >>>!!!>>> As part of a broader NLM reorganization, most of NLM's toxicology information services have been integrated into other NLM products and services.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
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.
<<<!!!<<< 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.
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CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.
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<<<!!!<<< The repository is no longer available. >>>!!!>>>The information is accessible through PubChem:https://pubchem.ncbi.nlm.nih.gov/. Help for HSDB Users in PubChem PDF: https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.pdf Help for HSDB Users in PubChem Web Page: https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.html <<<!!!>>>