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Found 11 result(s)
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
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The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) and German Plant Phenotyping Network (DPPN) has jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.
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.
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The China National GeneBank database (CNGBdb) is a unified platform for biological big data sharing and application services. CNGBdb has now integrated a large amount of internal and external biological data from resources such as CNGB, NCBI, and the EBI. There are several sub-databases in CNGBdb, including literature, variation, gene, genome, protein, sequence, organism, project, sample, experiment, run, and assembly. Based on underlying big data and cloud computing technologies, it provides various data services, including archive, analysis, knowledge search, and management authorization of biological data. CNGBdb adopts data structures and standards of international omics, health, and medicine, such as The International Nucleotide Sequence Database Collaboration (INSDC), The Global Alliance for Genomics and Health GA4GH (GA4GH), Global Genome Biodiversity Network (GGBN), American College of Medical Genetics and Genomics (ACMG), and constructs standardized data and structures with wide compatibility. All public data and services provided by CNGBdb are freely available to all users worldwide. CNGB Sequence Archive (CNSA) is the bionomics data repository of CNGBdb. CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in life science, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, and Sequence. Moreover, CNSA has achieved the correlation of sample entities, sample information, and analyzed data on some projects. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in the life science of CNGBdb, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, Sequence. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.
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National Genomic Resources Repository is established as an institutional framework for methodical and centralized efforts to collect, generate, conserve and distribute genomic resources for agricultural research.
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Database of forestry research installations in Canada with a focus on tree-level datasets (dendrometry, physical properties, dendrochronology, phenology, etc.).
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LIVIVO is an interdisciplinary search engine for literature and information in the field of life sciences. It is run by ZB MED – Information Centre for Life Sciences. LIVIVO automatically searches for the terms you enter in a central index of all the databases. The ZB MED Searchportal already provides a large amount of research data from DataCite data centres (e.g. Beijing Genomics Institute, Natural Environment Research Council) in the field of life sciences. These can be searched directly using the "Documenttype=research data" filter. A further integration of data from life science data repositories is planned.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
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The National Center for Forestry and Grassland Genetic Resources (Forestry and Grassland Repository) consists of a series of in situ and ex situ repositories and ex situ repositories, including 15 in situ repositories, 137 ex situ repositories and 3 facility repositories (attached), all of which are recognized by the Seedling Department of the State Forestry and Grassland Administration or the National Forestry Germplasm Resource Platform to collect and preserve forest, grass, flower, bamboo and rattan germplasm resources, and to establish a big data system through standardization, digitization. The purpose of the Forestry and Grassland Resource Bank is to strengthen the germplasm resources of forests, grasses, flowers, bamboos and rattan. The purpose of the Forestry and Grass Resource Bank is to strengthen the collection and preservation of forestry germplasm resources and open sharing, and to promote sustainable use; the objective is to use ultra-low temperature freezing, genomics, artificial intelligence and other high technology to carry out long-term preservation, accurate identification and in-depth exploration of germplasm resources, and to achieve safe preservation and efficient use of germplasm resources. The Forestry and Grassland Resource Bank undertakes the rendezvous of scientific and technological projects in the forestry germplasm resource category. By building an integrated sharing service platform for germplasm resource production, academia and research, it improves the innovation and exploitation capacity of forestry germplasm resources, supports major national needs in scientific research, ecological construction and economic development, promotes the docking of resources and needs, and facilitates the use of resources and the transformation of results. It realizes information and physical sharing, so that forest germplasm resources can be safely preserved and scientifically utilized.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.