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Found 10 result(s)

MaizeGDB

Maize Genetics and Genomics Database

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The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.

dbSNP

SNV

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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***

UniGene

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<<<!!!<<< This repository is no longer available>>>!!!>>>. Although the web pages are no longer available, you will still be able to download the final UniGene builds as static content from the FTP site https://ftp.ncbi.nlm.nih.gov/repository/UniGene/. You will also be able to match UniGene cluster numbers to Gene records by searching Gene with UniGene cluster numbers. For best results, restrict to the “UniGene Cluster Number” field rather than all fields in Gene. For example, a search with Mm.2108[UniGene Cluster Number] finds the mouse transthyretin Gene record (Ttr). You can use the advanced search page https://www.ncbi.nlm.nih.gov/gene/advanced to help construct these searches. Keep in mind that the Gene record contains selected Reference Sequences and GenBank mRNA sequences rather than the larger set of expressed sequences in the UniGene cluster.

TreeGenes

A forest tree genome database

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TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.

modENCODE

Model Organism ENCyclopedia of DNA Elements

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<<<!!!<<< As of 2023, support to maintain the www.modencode.org and intermine.modencode.org sites have been retired following the end of funding. To access data from the modENCODE project, or for questions regarding the data they make available, please visit these databases: Fly data: FlyBase: ModENCODE data at FlyBase: https://wiki.flybase.org/wiki/FlyBase:ModENCODE_data_at_FlyBase FlyBase: https://www.re3data.org/repository/r3d100010591 Worm data: WormBase https://www.re3data.org/repository/r3d100010424 Data, including modENCODE and modERN project data, is also available at the ENCODE Portal: https://www.re3data.org/repository/r3d100013051 (search metadata and view datasets for Drosophila and Caenorhabditis https://www.encodeproject.org/matrix/?type=Experiment&control_type!=*&status=released&replicates.library.biosample.donor.organism.scientific_name=Drosophila+melanogaster&replicates.library.biosample.donor.organism.scientific_name=Caenorhabditis+elegans&replicates.library.biosample.donor.organism.scientific_name=Drosophila+pseudoobscura&replicates.library.biosample.donor.organism.scientific_name=Drosophila+mojavensis). >>>!!!>>>

Network for the Detection of Atmospheric Composition Change

NDACC

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The Network for the Detection of Atmospheric Composition Change (NDACC), a major contributor to the worldwide atmospheric research effort, consists of a set of globally distributed research stations providing consistent, standardized, long-term measurements of atmospheric trace gases, particles, spectral UV radiation reaching the Earth's surface, and physical parameters, centered around the following priorities.

UCSD Metabolomics Workbench

Metabolomics Workbench

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With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.

EOL

Earth Observing Laboratory

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EOL’s platforms and instruments collect large and often unique data sets that must be validated, archived and made available to the research community. The goal of EOL data services is to advance science through delivering high-quality project data and metadata in ways that are as transparent, secure, and easily accessible as possible - today and into the future. By adhering to accepted standards in data formats and data services, EOL provides infrastructure to facilitate discovery and direct access to data and software from state-of-the-art commercial and locally-developed applications. EOL’s data services are committed to the highest standard of data stewardship from collection to validation to archival.

NCBI Trace Archive

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<<<!!!<<< This repository is no longer available. (Trace Archive is scheduled to retire on June 17, 2022) >>>!!!>>>

GAGE

Geodetic Facility for the Advancement of Geoscience

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UNAVCO promotes research by providing access to data that our community of geodetic scientists uses for quantifying the motions of rock, ice and water that are monitored by a variety of sensor types at or near the Earth's surface. After processing, these data enable millimeter-scale surface motion detection and monitoring at discrete points, and high-resolution strain imagery over areas of tens of square meters to hundreds of square kilometers. The data types include GPS/GNSS, imaging data such as from SAR and TLS, strain and seismic borehole data, and meteorological data. Most of these can be accessed via web services. In addition, GPS/GNSS datasets, TLS datasets, and InSAR products are assigned digital object identifiers.