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Found 8 result(s)
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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.
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iDog, an integrated resource for domestic dog (Canis lupus familiaris) and wild canids, provides the worldwide dog research community a variety of data services. This includes Genes, Genomes, SNPs, Breed/Disease Traits, Gene Expressions, Single Cell, Dog-Human Homolog Diseases and Literatures. In addition, iDog provides Online tools for performing genomic data visualization and analyses.
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eLMSG (eLibrary of Microbial Systematics and Genomics) is a web microbial library that integrates not only taxonomic information, but also genomic information and phenotypic information (including morphology, physiology, biochemistry and enzymology). The taxonomic system of eLMSG is manually curated and composed of all validly and some effectively published taxa. For each taxon, the Latin name, taxon ID (NCBI taxonomy), etymology, rank, lineage, the dates of effective and/or valid publication, feature descriptions, nomenclature type and references for the proposal and emendations during the history of the taxon are presented. Besides these data, the species taxa contain information about 16S rRNA gene and/or genome sequences. All publicly available genome data of each type species including both type and non-type strains were collected, and if needed, re-annotated using the standardized analysis pipeline. Furthermore, pan-genomic data analyses were conducted for species with ≥5 genome sequences available. Finally, for all type species, taxonomically relevant phenotypic data were extracted and curated from literatures, which were further indexed into eLMSG as searchable and analyzable data records. Taken together, eLMSG is a comprehensive web platform for studying mi- crobial systematics and genomics, potentially useful for better understanding microbial taxonomy, natural evolutionary processes and ecological relationships.
The National Earth Observation Science Data Center, whose predecessor was the National Integrated Earth Observation Data Sharing Platform, has formed a sustainable, cross-agency, one-stop data sharing service capability after years of construction, and it is also the main channel for international exchange of remote sensing data in China. In the future, it will manage and coordinate scientific data resources in the field of earth observation on behalf of the country, and build a national-level earth observation big data infrastructure. Coordinate various industry data centers, scientific research institutions and enterprises in the field of Earth observation in China to cooperate in building a national strategic, fundamental, scientific, internationalized, and independent and controllable scientific big data environment in the field of Earth observation. On the basis of the already formed data ecology and cooperation mechanism, data sharing services, and international data cooperation, we will actively expand to the whole life cycle management of data and carry out data management work such as the collection, management, analysis and mining, and sharing services of national scientific data resources for Earth observation. Form a unified technical support system and data sharing service environment for Earth observation data in China. Maintain and enhance its international influence and become a domestic and international first-class scientific data center for Earth observation!
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MTD is focused on mammalian transcriptomes with a current version that contains data from humans, mice, rats and pigs. Regarding the core features, the MTD browses genes based on their neighboring genomic coordinates or joint KEGG pathway and provides expression information on exons, transcripts, and genes by integrating them into a genome browser. We developed a novel nomenclature for each transcript that considers its genomic position and transcriptional features.
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
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China Meteorological Data Service Center, an upgraded system of the meteorological data sharing network, is an important component of the underlying national science and technology platform and a main portal application system of meteorological cloud. It is an authoritative and unified shared service platform for China Meteorological Administration to open its meteorological data resources to domestic and global users, and a data supporting platform for China to open its meteorological service market and promote the sharing and efficient application of meteorological information resources as a new meteorological service system. The comprehensive meteorological database provide online and offline shared services, the existing data types including global upper-air sounding data, surface observations, ocean observations, numerical forecast products, agro-meteorological data of ground observation data encryption, aircraft soundings, numerical weather prediction analysis field data, GPS-Met, Storm 2 No, GOES-9 satellite data, soil moisture, aircraft reported sandstorm monitoring, TOVS, ATOVS, wind profilers, satellite detection information.
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The National Stem Cell Translational Resource Bank (NSCTRB) contains various stem cell resources of both clinical and research grade, especially a sub-bank composed with HLA high-frequency iPSC lines in which the HLA types could match more than 60% of the Chinese population. It can not only provide services to stem cell clinical researches and translation applications, but also provide effective resources for scientific research to the Universities, research institutes, companies, etc. The bank has complete standards, specifications and relevant management systems, and has more than 200 perfessonals in the field of stem cells.