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Found 54 result(s)
The Northern California Earthquake Data Center (NCEDC) is a permanent archive and distribution center primarily for multiple types of digital data relating to earthquakes in central and northern California. The NCEDC is located at the Berkeley Seismological Laboratory, and has been accessible to users via the Internet since mid-1992. The NCEDC was formed as a joint project of the Berkeley Seismological Laboratory (BSL) and the U.S. Geological Survey (USGS) at Menlo Park in 1991, and current USGS funding is provided under a cooperative agreement for seismic network operations.
The primary function of this database is to provide authoritative information about meteorite names. The correct spelling, complete with punctuation and diacritical marks, of all known meteorites recognized by the Meteoritical Society may be found in this compilation. Official abbreviations for many meteorites are documented here as well. The database also contains status information for meteorites with provisional names, and listings for specimens of doubtful origin and pseudometeorites. A seconday purpose of this database is to provide an interface to map services for the display of geographic information about meteorites. Two are currently implemented here. If the user has installed the free NASA program World Wind, links are provided for each meteorite to zoom the program to the find location. The database also provides links to the Google Maps service for the display of find locations.
>>>!!!<<< The repository is no longer available. >>>!!!<<< Here you will find a collection of atomic microstructures that have been built by the atomic modeling community. Feel free to download any of these and use them in your own scientific explorations.The focus of this cyberinfrastructure is to advance the field of atomic-scale modeling of materials by acting as a forum for disseminating new atomistic scale methodologies, educating non-experts and the next generation of computational materials scientists, and serving as a bridge between the atomistic and complementary (electronic structure, mesoscale) modeling communities.
SeaBASS, the publicly shared archive of in situ oceanographic and atmospheric data maintained by the NASA Ocean Biology Processing Group (OBPG). High quality in situ measurements are prerequisite for satellite data product validation, algorithm development, and many climate-related inquiries. As such, the NASA Ocean Biology Processing Group (OBPG) maintains a local repository of in situ oceanographic and atmospheric data to support their regular scientific analyses. The SeaWiFS Project originally developed this system, SeaBASS, to catalog radiometric and phytoplankton pigment data used their calibration and validation activities. To facilitate the assembly of a global data set, SeaBASS was expanded with oceanographic and atmospheric data collected by participants in the SIMBIOS Program, under NASA Research Announcements NRA-96 and NRA-99, which has aided considerably in minimizing spatial bias and maximizing data acquisition rates. Archived data include measurements of apparent and inherent optical properties, phytoplankton pigment concentrations, and other related oceanographic and atmospheric data, such as water temperature, salinity, stimulated fluorescence, and aerosol optical thickness. Data are collected using a number of different instrument packages, such as profilers, buoys, and hand-held instruments, and manufacturers on a variety of platforms, including ships and moorings.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
<<<!!!<<< This repository is no longer available. >>>!!!>>> NetPath is currently one of the largest open-source repository of human signaling pathways that is all set to become a community standard to meet the challenges in functional genomics and systems biology. Signaling networks are the key to deciphering many of the complex networks that govern the machinery inside the cell. Several signaling molecules play an important role in disease processes that are a direct result of their altered functioning and are now recognized as potential therapeutic targets. Understanding how to restore the proper functioning of these pathways that have become deregulated in disease, is needed for accelerating biomedical research. This resource is aimed at demystifying the biological pathways and highlights the key relationships and connections between them. Apart from this, pathways provide a way of reducing the dimensionality of high throughput data, by grouping thousands of genes, proteins and metabolites at functional level into just several hundreds of pathways for an experiment. Identifying the active pathways that differ between two conditions can have more explanatory power than just a simple list of differentially expressed genes and proteins.
The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. In addition to capturing the core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and clear indications of the quality of annotation in the form of evidence attribution of experimental and computational data. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. The UniProt Knowledgebase,is an expertly and richly curated protein database, consisting of two sections called UniProtKB/Swiss-Prot and UniProtKB/TrEMBL.
>>>!!!<<< 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 Johns Hopkins Research Data Repository is an open access repository for Johns Hopkins University researchers to share their research data. The Repository is administered by professional curators at JHU Data Services, who will work with depositors to enable future discovery and reuse of your data, and ensure your data is Findable, Accessible, Interoperable and Reusable (FAIR). More information about the benefits of archiving data can be found here: https://dataservices.library.jhu.edu/
MycoCosm, the DOE JGI’s web-based fungal genomics resource, which integrates fungal genomics data and analytical tools for fungal biologists. It provides navigation through sequenced genomes, genome analysis in context of comparative genomics and genome-centric view. MycoCosm promotes user community participation in data submission, annotation and analysis.
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
BioPortal is an open repository of biomedical ontologies, a service that provides access to those ontologies, and a set of tools for working with them. BioPortal provides a wide range of such tools, either directly via the BioPortal web site, or using the BioPortal web service REST API. BioPortal also includes community features for adding notes, reviews, and even mappings to specific ontologies. BioPortal has four major product components: the web application; the API services; widgets, or applets, that can be installed on your own site; and a Virtual Appliance version that is available for download or through Amazon Web Services machine instance (AMI). There is also a beta release SPARQL endpoint.
PWT version 10.0 is a database with information on relative levels of income, output, input and productivity, covering 183 countries between 1950 and 2019.
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Results from time-series analysis of Landsat images in characterizing global forest extent and change from 2000 through 2016.
Giardia lamblia is a significant, environmentally transmitted, human pathogen and an amitochondriate protist. It is a major contributor to the enormous worldwide burden of human diarrheal diseases, yet the basic biology of this parasite is not well understood. No virulence factor has been identified. The Giardia lamblia genome contains only 12 million base pairs distributed onto five chromosomes. Its analysis promises to provide insights about the origins of nuclear genome organization, the metabolic pathways used by parasitic protists, and the cellular biology of host interaction and avoidance of host immune systems. Since the divergence of Giardia lamblia lies close to the transition between eukaryotes and prokaryotes in universal ribosomal RNA phylogenies, it is a valuable, if not unique, model for gaining basic insights into genetic innovations that led to formation of eukaryotic cells. In evolutionary terms, the divergence of this organism is at least twice as ancient as the common ancestor for yeast and man. A detailed study of its genome will provide insights into an early evolutionary stage of eukaryotic chromosome organization as well as other aspects of the prokaryotic / eukaryotic divergence.
CDAAC is responsible for processing the science data received from COSMIC. This data is currently being processed not long after the data is received, i.e. approximately eighty percent of radio occultation profiles are delivered to operational weather centers within 3 hours of observation as well as in a more accurate post-processed mode (within 8 weeks of observation).
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.
Originally named the Radiation Belt Storm Probes (RBSP), the mission was re-named the Van Allen Probes, following successful launch and commissioning. For simplicity and continuity, the RBSP short-form has been retained for existing documentation, file naming, and data product identification purposes. The RBSPICE investigation including the RBSPICE Instrument SOC maintains compliance with requirements levied in all applicable mission control documents.
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.
<<<!!!<<< 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.
TAED is a database of phylogenetically indexed gene families. It contains multiple sequence alignments from MAFFT1, maximum likelihood phylogenetic trees from PhyML2, bootstrap values for each node, dN/dS ratios for each lineage from the free ratios model in PAML3, and labels for each node of speciation or duplication from gene tree/species tree reconciliation using SoftParsMap4. The phylogenetic indexing enables simultaneous viewing of lineages with high dN/dS that occurred along the same species tree branches. Resources from the Protein Data Bank (PDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG)5, have been incorporated into the TAED analysis to detect substitutions along each branch within the phylogenetic tree and to assess selection within pathways.